Shake it Out – Embracing the Future in Program Management – Part One: Program and Project Management in the Public Interest

I heard the song from which I derived the title to this post sung by Florence and the Machine and was inspired to sit down and write about what I see as the future in program management.

Thus, my blogging radio silence has ended as I begin to process and share my observations and essential achievements over the last couple of years.

Some of my reticence in writing has been due to the continual drumbeat of both outrageous and polarizing speech that had dominated our lives for four years. Combined with the resulting societal polarization, I was overwhelmed by the hyper-politicized environment which has fostered disinformation and dysfunction. Those who wish to seek my first and current word on this subject need only visit my blog post, “In Defense of Empiricism” at the AITS Blogging Alliance here.

It is hard to believe that I published that post four years ago. I stand by it today and believe that it remains as valid, if not more so, than it did when I wrote and shared it.

Finally, the last and most important reason for my relative silence has been that I have been hard at work putting my money and reputation where my blogging fingers have been—in the face of a pandemic that has transformed and transfigured our social and economic lives.

My company—the conduit that provides the insights I share here—is SNA Software LLC. We are a small, veteran-owned company and we specialize in data capture, transformation, contextualization and visualization. We do it in a way that removes significant effort in these processes, ensures reliability and trust, to incorporate off-the-shelf functionality that provides insight, and empowers the user by leveraging the power of open systems, especially in program and project management.

Program and Project Management in the Public Interest

There are two aspects to the business world that we inhabit: commercial and government; both, however, usually relate to some aspect of the public interest, which is our forte.

There are also two concepts about this subject to unpack.

The first is distinguishing between program and project management. In this concept, a program is an overarching effort that may consist of individual efforts that, together, will result in the production or completion of a system, whether that is a weapons system, a satellite, a spacecraft, or an engine. It could even be a dam or some other aspect of public works.

A project under this concept is a self-contained effort separated organizationally from the larger entity, which possesses a clearly defined start and finish, a defined and allocated budget, and a set of plans, a performance management feedback system, and overarching goals or “framing assumptions” that define what constitutes the state of being “done.”

Oftentimes the terms “program” and “project” are used interchangeably, but the difference for these types of efforts is important and goes beyond a shallow understanding of the semantics. A program will also consider the lifecycle of the program: the follow-on logistics, the interrelationship of the end item to other components that will constitute the deployed system or systems, and any iterative efforts relating to improvement, revision, and modernization.

A word on the term “portfolio” is also worth a mention in the context of our theme. A portfolio is simply a summary of the projects or programs under an organizational entity that has both reporting and oversight responsibility for them. They may be interrelated or independent in their efforts, but all must report in some way, either due to fiduciary, resource, or oversight concerns, to that overarching entity.

The second concept relates to the term “public interest.” Programs and projects under this concept are those that must address the following characteristics: legality, governance, complexity, integrity, leadership, oversight, and subject matter expertise. I placed these in no particular order.

What we call in modern times “public interest” was originally called “public virtue” by the founders of the United States, which embody the ideals of the American Revolution, and upon which our experiment in democratic republicanism is built. It consists of conducting oneself in a manner in which the good of the whole—the public—outweighs personal interests and pursuits. Self-dealing need not apply.

This is no idealistic form of self-delusion: I understand, as do my colleagues, that we are, at heart, a commercial profit-making enterprise. But the manner in which we engage with government requires a different set of rules and many of these rules are codified in law and ethical practice. While others do not always feel obliged to live by these rules, we govern ourselves and so choose to apply these virtues—and to seek to support and change our system to encourage such behavior to as to be the norm—even in direct interactions with government personnel where we feel these virtues have been violated.

Characteristics of Public Interest Programs

Thus, the characteristics outlined above apply to program and project management in the public interest in the following manner:

Legality: That Public Interest Programs are an artifact of law and statute and are specifically designed to benefit the public as a whole.

At heart, program and project management are based on contractual obligations, whether those instruments apply internally or externally. As a result, everyone involved in the program and project management discipline is, by default, part of the acquisition community and the acquisition process. The law that applies to all government acquisition systems is based on the Federal Acquisition Regulation (FAR). There are also oversight and fiduciary responsibilities that apply as a result of the need for accountability under the Congressional appropriations process as well as ethical standards that apply, such as those under the Truth in Negotiations Act (TINA). While broad in the management flexibility they allow, violations of these statutes come with serious consequences. Thus, as a basis for establishing hard and fast guardrails in the management of programs and projects. Individual government agencies and military services also publish additional standards that supplement the legal requirements. An example is the Department of Defense FAR Supplement (DFARS). Commercial entities that hold government contracts in relation to Program Management Offices (PMOs) must sign on to both FAR and agency contractual clauses, which will then flow down to their subcontractors. Thus, the enforcement of these norms is both structured and consistent.

Governance: That the Organizational Structure and Disciplines deriving from Public Interest Programs are a result of both Contract and Regulatory Practice under the concept of Government Sovereignty.

The government and supplier PMOs are formed as a result of a contractual obligation for a particular purpose. Government contracting is unique since government entities are the sovereign. In the case of the United States, the sovereign is the elected government of the United States, which derives its legitimacy from the people of the United States as a whole. Constitutionally, the Executive Branch is tasked with the acquisition responsibility, but the manner and method of this responsibility is defined by statute.

Thus, during negotiations and unlike in commercial practice, the commercial entity is always the offeror and the United States always the party that either accepts or rejects the offer (the acceptor). This relationship has ramifications in contract enforcement and governance of the effort after award. It also allows the government to dictate the terms of the award through its solicitations. Furthermore, provisions from law establish cases where the burden for performance is on the entity (the supplier) providing the supplies and services.

Thus, the establishment of the PMO and oversight organizations have a legal basis, aside from considerations of best business practice. The details of governance within the bounds of legal guidance are those that apply through agency administrative law and regulation, oftentimes based on best business practice. These detailed practices of governance are usually established as a result of hard-learned experience: establishment of disciplines (systems engineering and technical performance, planning, performance management, cost control, financial execution, schedule, and progress assessment), the periodicity of reporting, the manner of oversight, the manner of liaison between the supplier and government PMOs, and alignment to the organization’s goals.

Complexity: That Public Interest Programs possess a level of both technical and organizational complexity unequaled in the private sector.

Program and project management in government involves a level of complexity rarely found in similar non-governmental commercial efforts. Aligning the contractual requirements, as an example, to an assessment of the future characteristics of a fighter aircraft needed to support the U.S. National Defense Strategy, built on the assessments by the intelligence agencies regarding future threats, is a unique aspect of government acquisition.

Furthermore, while relying on the expertise of private industry of such systems that support national defense, as well as those that support space exploration, energy, and a host of other needs, the items being acquired, which require cost type R&D contracts that involve program management, by definition are those where the necessary solutions are not readily available as commercial end items.

Oftentimes these requirements are built onto and extend existing off-the-shelf capabilities. But given that government investment in R&D represents the majority of this type of spending in the economy, absent it, technology and other efforts directed to meeting defense, economic, societal, climate, and space exploration challenges of the future would most likely not be met—or those that do will benefit only a portion of the populace. The federal government uniquely possesses the legal legitimacy, resources, and expertise to undertake such R&D that, pushing the envelope on capabilities, involves both epistemic and aleatory risk that can be managed through the processes of program management.

Integrity: The conduct of Public Interest Programs demands the highest level of commitment to a culture of accountability, impartiality, ethical conduct, fiduciary responsibility, democratic virtues, and honesty.

The first level of accountability resides in the conduct of the program manager, who is the locus of integrity within the program management office. This requires a focus on the duties the position demands as a representative of the Government of the United States. Furthermore, the program manager must ensure that the program team operate within the constraints established by the program’s or project’s contractual commitments, and that it continues to work to meeting the program goals that align with the stated interests and goals of the organization. That these duties are exercised regardless of self-interest is the basis of integrity.

This is not an easy discipline, and individuals oftentimes cannot separate their own interests from those of their duties. Yet, without this level of commitment, the legitimacy of the program office and the governmental enterprise itself is threatened.

In prior years, as an active-duty Supply Corps officer, I came across cases where individuals in civil service or among the commissioned officer community confused their own interests—for promotion, for self-aggrandizement, for ego—with those duties demanded of their rank or position. Such confusions of interests are serious transgressions. With contracted-out positions within program offices adding consulting and staffing firms into the mix, with their oftentimes diversified interests and portfolios, an additional layer of challenges is presented. Self-promotion, competition, and self-dealing have all too often become blatant, and program managers would do well to enforce strict rules regarding such behavior.

The pressures of exigency are oftentimes the main cause of the loss of integrity of the program or project. Personal interrelationships and human resource management issues can also undermine good order and discipline necessary for the program or project to organize itself into a cohesive, working team that is focused on a common vision.

Key elements mentioned in our opening thesis regarding ethical conduct, adherence to democratic virtues which include acceptance of all members of the team regardless of color, ethnicity, race, sexual identity, religion, or place of national origin. People deserve the respect and decency deriving from their basic human rights to enjoy human dignity, as well as of their position. Adding to these elements include honesty and the willingness to accept and report bad news, which is essential to integrity.

An organization committed to the principle of accountability will seek to measure and ensure that the goals of the program or project are being met, and that ameliorative measures are taken to correct any deficiencies. Since these efforts oftentimes involve years of effort involving significant sums of public monies, fiduciary integrity is essential to this characteristic.

All of these elements can and should exist in private, commercial practices. The difference that makes this a unique characteristic to program management in the public interest is the level of scrutiny, reporting, and review that is conducted: from oversight agencies within the Executive Department of the government, to the Congressional oversight, hearing and review processes, agency review, auditing and reporting, and inquires and critiques by the press and the public. Public interest program management is life in a fishbowl, except in the most secret efforts, and even those will eventually be subject to scrutiny.

As with a U.S. Navy ship that makes a port of call in a foreign country, the actions of the conduct of crew will not only reflect on themselves or their ship, but on the United States; so it is also with our program offices. Thus, systems of programmatic governance and business management must anticipate in their structure the level of adherence required. Given the inherent level of risk involved in these efforts, and given the normal amount of error human systems create even with good intentions and expertise, establishing a system committed to the elements of integrity creates a self-correcting one better prepared to meet the program’s or project’s challenges.

Leadership: Programs in the Public Interest differ from equivalent commercial efforts in that management systems and incentives based on profit- and shareholder-orientations do not exist. Instead, a special kind of skillset is required that includes good business management principles and skills combined with highly developed leadership traits.

Management skills tend to be a subset of leadership, though in business schools and professional courses they tend to be addressed as co-equal. This is understandable in commercial enterprises that focus on the capitalistic pressures regarding profit and market share.

Given the unique pressures imposed by the elements of integrity, the program manager and the program team are thrown into a situation that requires a focus on the achievement of organizational goals. In the case of program and project management, this will be expressed in the form of a set of “framing assumptions” that roll into an overarching vision.

A program office, of course, is more than a set of systems, practices, and processes. It is, first and foremost, a collection of individuals consisting of subject matter experts and professionals who must be developed into a team committed to the vision. The effort to achieve this team commitment is one of the more emotional and compelling elements that comprise leadership.

Human systems are adaptive ones, complex, which react and are created by both incentives and sanctions. Every group, especially involving creative and talented people, starts out being a collection of individuals with the interrelations among the members in an immature state. Underlying the expression of various forms of ambition and self-identification among mature individuals is the basic human need for social acceptance, born from the individual personal need for love. This motivation exists psychologically in all individuals except for sociopaths. It is also the basis for empathy and the acceptance of the autonomy of others, which form the foundation for team building.

The goal of the leader is to encourage maturity among the members of the group. The result is to create that overused term “synergy.” This is accomplished by doing those things as a leader necessary to develop members of the group that fosters trust, acceptance, and mutual respect. Admiral James L. Holloway, Jr., in his missive on Naval Leadership, instructed his young officers to eschew any concept of perfectionism in people. People make mistakes. We know this if we are to be brutally honest about our own experiences and actions.

Thus, intellectual honesty and an understanding on what motivates people within their cultural mores, above all else, is essential to good leadership. Americans, by nature, tend to be skeptical and independently minded. They require a level of explanation and due diligence that is necessary to win over their commitment to a goal or vision. When it comes to professionals operating within public service in government—who take an oath to the Constitution and our system of laws—the ability to lead tends to be more essential than just good management skills, though the latter are by no means unimportant. Management in private enterprise assumes a contentious workplace of competing values and interests, and oftentimes fosters it.

Program and project management in the public interest cannot succeed in such an environment. It requires a level of commitment to the goals of the effort regardless of personal values or interests among the individual members of the team. That they must be convinced to this level of commitment ensures that the values of leadership not only operate at the top of the management chain, but also at each of the levels and lateral relationships that comprise the team.

The shorthand for leadership in this culture is that the leader is “working their way out of their job,” and “that in order to be a good leader one must be a good follower,” meaning that all members of the team are well-informed, that their contributions, expertise and knowledge is acknowledged and respected, that individual points of failure through the irreplaceable person syndrome are minimized, and that each member of a team or sub-team can step in or step up to keep the operation functioning. The motivating concept in these situations are the interests of the United States, in lieu of a set of stockholders or some fiduciary reward.

Finally, there is the concept of the burden of leadership. Responsibility can be can be delegated, but accountability cannot. Leadership in this context entails an obligation to take responsibility for both the mission of the organization and the ethical atmosphere established in its governance.

Oversight: While the necessity for integrity anticipates the level of accountability, scrutiny, oversight, and reporting for Programs in the Public Interest, the environment this encompasses is unique compared to commercial entities.

The basis for acquisition at the federal level resides in the Article Two powers of the president as the nation’s Chief Executive. Congress, however, under its Article One powers, controls appropriations and passes laws related to the processes, procedures and management of the Executive Branch.

Flowing from these authorities, the agencies within the federal government have created offices for the oversight of the public’s money, the methods of acquisition of supplies and services, and the management of contracts. Contracting Officers are given authority through a warrant to exercise their acquisition authority under the guidance and management of a senior acquisition authority.

Unlike in private business, the government operates under the concept of Actual Authority. That is, no one may commit the government except those possessing a warrant. Program Managers are appointed to provide control and administration of cost type efforts, especially those containing R&D, to shepherd these efforts over the course of what usually constitutes a multi-year effort. The Contracting Officer and/or the senior acquisition authority in these cases will delegate contract administration authority to the Program Manager. As such, it is a very powerful position.

The inherent powers of the Executive Branch and the Legislative Branches of government create a tension that is resolved through a separation of powers and the ability of one branch to—at least in most cases—check the excesses and abuses of the other: the concept of checks and balances, especially through the operation of oversight.

When these tensions cannot be resolved within the processes established for separation of powers, the third branch of government becomes involved: this is the Judicial Branch. The federal judiciary has the ability to review all laws of the United States, their constitutionality, and their adherence to the letter of the law in the case of statute.

Wherever power exists within the federal government there exists systems of checks and balances. The reason for this is clear, and Lord Acton’s warning about power corrupting and absolute power corrupting absolutely is the operational concept.

Congress passes statutes and the Judiciary interprets the law, but it is up to the Executive Branch through the appointed heads of the various departments of government down through the civil service and, in the case of the Department of Defense, the military chain of command under civilian authority, to carry out the day-to-day activities in executing the laws and business of the government. This creates a large base of administrative law and procedure.

Administrative Law and the resulting procedures in their implementation come about due to the complexities in the statutes themselves, the tests of certain provisions of the statutes in the interplay between the various branches of government, and the practicalities of execution. This body of law and procedure is oftentimes confused with “regulation” in political discussions, but it is actually the means of ensuring that the laws are faithfully executed without undue political influence. It is usually supplemented by ethical codes and regulations as well.

As a part of this ecosystem, the Program in the Public Interest must establish a discipline related to self-regulation, due diligence, good business practice, fiduciary control, ethical and professional conduct, responsibility, and accountability. Just as the branches of the federal government are constructed to ensure oversight and checks-and-balances, this also exists with normative public administration within the Executive Branch agencies.

This is often referred to both positively and, mostly among political polemicists in the negative, as the bureaucracy. The development of bureaucracies in government is noted by historians and political scientists as an indication of political stability, maturity, and expertise. Without bureaucracies, governments tend to be capricious and their policies uncertain. The practice of stare decisis—the importance of precedent in legal decisions—is also part and parcel of stability. Government power can be beneficial or coercive. Resting action on laws and not the whims or desires of the individual person is essential to the good order and discipline of the federal government.

As such, program and project managers, given the extensive latitude and inherent powers of their position, are subject to rigorous reporting, oversight, and accountability regimes in the performance of their duties. In R&D cost-type program and project management efforts, the risk is shared between the supplier and the government. And the government flows down this same regime to the contractor to ensure the integrity of the effort in the expenditure of public monies and under the performance and delivery of public contacts.

This leads us to the last important aspect of oversight: public scrutiny, which also includes the press as the Fourth Estate. When I was a young Lieutenant in the Navy working in contracts the senior officer to whom I was assign often remarked: “Never do anything that would cause you to be ashamed were it to end up being read by your grandmother in the Washington Post.”

Unlike private business where law, contractual obligation, and fiduciary responsibility are the main pressures on tolerated behavior, the government and its actions are—and must be—under constant public scrutiny. It is expected. Senior managers who champ against the bit of this check on official conduct misunderstand their role. Even the appearance of malfeasance or abuse can cause one to steer into the rocks and shoals.

Subject Matter Expertise: Given the interrelated characteristics of legality, governance, complexity, integrity, leadership, and oversight—linked to the development of a professional, permanent bureaucracy acting through a non-partisan civil service—the practices necessary to successfully shepherd such efforts has produced areas of expertise and specialization. These areas provide a basis for leveraging technology in gaining insight into meeting all of the requirements necessary to the good administration and control of Program Management in the Public Interest.

The structures and practices of program and project management are reflected in the private economy. Some of this is contractually prescribed and some of it is based on best business practice learned through hard experience. In the interplay of government and industry, most often an innovation in one has been refined and improved in the other, only to find its way back to practice on the originating “side” of the transaction.

Initially in our history this cross-fertilization occurred through extraordinary wartime measures: standardization of rifled weaponry passed down by Thomas Jefferson and Eli Whitney, and for railroad track gauge standards issued by the Union government during the Civil War, are just two examples that turned out to provide a decisive advantage against laissez faire and libertarian approaches.

As the complexity of private business concerns, particularly in the international sphere, began to mimic—and in many cases surpass—the size and technical complexity of many individual government efforts, partnerships with civil authorities and private businesses saw the need for industry standardization for both electrical and non-electrical components and processes. The former was particularly important in the “Current Wars” between Edison and Westinghouse.

These simple and earlier examples highlight the great conundrum of standardization of supply, practice and procedure in acquisition: the need for economy through competition of many sources for any particular commodity or item weighed against the efficiency and interoperability needed to continue operations. Buying multiple individual items with the same function but produced using differing standards creates a nightmare of suboptimization. Overly restrictive standards can and have had the effect of reducing competition and stifling innovation, especially if the standard is proprietary.

In standards setting there are several interests involved that must be taken into account: the technical expertise (technical, qualitative, etc.) that underlies the standard, the public interest in ensuring a healthy marketplace that rewards innovation, diversity, and price competitiveness, the need for business-to-business cooperation and synergy in the marketplace, and the preponderance of practice, among others. In the Defense industry this also includes national security concerns.

This last consideration provides an additional level of tension between private industry and government interests. In the competition for market share and market niches, businesses are playing a zero-sum game that shifts between allies and competitors. Still, the interest of individual actors is focused on making a proprietary product or service dominant in the target market.

Government, on the other hand, particularly one that operates as a republic based on democratic processes and virtues and a commitment to equal rights, has a different set of interests that are, in many cases, diametrically opposed to those of individual players in the marketplace. Government needs and desires a broad choice of sources for what it needs, while ensuring that qualitative standards are met under a fair and reasonable price. When it does find innovation, it seeks to reward it, but only for the limited terms, conditions, and period of the contractual instrument.

The greater the risk in these cases—especially when cost risk is shared—the greater the need for standards, especially qualitative ones. The longer the term of the effort, the greater the need for checks and balances through evaluation, review, and oversight. The greater the dollar value, the greater importance for fiduciary and contractual accountability.

Thus, subject matter expertise has evolved over time, aligned with the functions and end items being developed and delivered. These areas include:

Estimating – A critical part of program and project management, this is a discipline with highly specialized quantitative methods for estimating and projecting project costs, resources, and duration. It is part of the planning phase prior to program or project inception. It can be used to support budget planning prior to program approval, during negotiations and, after award, to inform the project plan.

Systems Engineering – as described by the International Council of Systems Engineering, “a transdisciplinary and integrative approach to enable the successful realization, use, and retirement of engineered systems, using systems principles and concepts, and scientific, technological, and management methods.”

As it relates to program and project management, the technical documents related to providing the basis and structure of the lifecycle management of the end item application, including the application of technical standards, measures of effectiveness, measures of performance, key performance parameters, and technical performance measures. In simplistic terms, systems engineering defines when the item under R&D reaches the state of “done.”

Financial Management – at the program and project management level, the planning, organizing, directing and controlling the financial activities such as procurement and utilization of funds to adhere to the limitations of law and consistent with the terms and conditions of the contract and the its ancillary planning and execution documents.

At its core, financial management within this discipline includes the planning, programming, budgeting, and execution process for the financial requirements of successful program execution. As with any individual enterprise, cashflow for required activities with the right type of money determined by Congressional appropriation presents a unique and specialized skillset under program management in the public interest. Oftentimes the lack of funds necessary to address a particular programmatic risk or challenge can be just as decisive to program execution and success as any technical challenge.

Risk and Uncertainty – the concept of risk and uncertainty have evolved over time. Under classical economics (both Keynes and Knight), risk is where all of the future events and consequences of an action are known, but where specific outcomes are unknown. As such, probability calculus is applied to determine the risk management: mitigation and handling. Uncertainty, under this definition, is unknowable events that will result from our actions and is implicit in human action. There is no probability calculus or risk buy-down that can address areas of uncertainty. These definitions are also accepted under the concept of complexity economics.

My good colleague Glen Alleman (2013) at his blog, Herding Cats, casts risk as a product of uncertainty. This is a reordering of definitions, but not unuseful. Under Glen’s approach, uncertainty is broken into aleatory and epistemic uncertainty. The first—aleatory—comes from a random process, what Keynes, Knight, et al. would define as classical uncertainty. The second—epistemic—comes from lack of knowledge. The first is irreducible, which is consistent with classical economics and complexity economics; the second is subject to probability analysis and risk handling methodologies.

Both risk and uncertainty—aleatory and epistemic—occur within all phases and under each discipline within the project management environment. Any human action involves these forces of cause-and-effect and uncertainty—and limit our actions under the concept of “free will.”

Planning and Scheduling – usually these have been viewed as separate entities, but they are, in fact, part of a continuum, as are all of the disciplines mentioned, but more on that later in these blogs.

Planning involves the ability to derive the products of both the contract terms and conditions, and the systems engineering process. The purpose is to develop a high-level, time-phased plan that captures program events, deliverables, requirements, significant accomplishment criteria, and basic technical performance management achievement that will be the basis for a more detailed integrated master schedule.

The scheduling discipline is tasked with further delineating the summary tasks into schedule activities based on critical path methodology. A common refrain when I worked on the government side of program management was that you cannot eat an elephant in one gulp: you have to eat it one piece at a time.

As it relates to this portion of project methodology, I have, over the years, heard people say that planning and scheduling is more of an art instead of a science. Yet, the artifacts upon which our planning documents rest exist as part of the acquisition process and our systems and procedures are mature and largely standardized. The methods of systems engineering are precise and consistent.

The lexicon of planning and scheduling, regardless of the software applications or manual methods used, describe the same phenomenon and concepts, despite slightly different—and oftentimes proprietary—terminology. The concept of critical path analysis is well documented in the literature with slight, though largely insignificant, differences in application.

What appears as art is, in reality, a process that involves a great deal of complexity because these are the documents upon which all of the moving parts of the program are documented. Rather than art, it is a discipline that requires attention to detail and collaboration, aside from the power of computing.

Resource Management – as with planning and scheduling, resource management consists of a detailed accounting of the people, equipment, monies, and suppliers that are required to achieve the activities detailed in the program schedule.

In the detailed and specialized planning of projects and programs in the public interest, these efforts are cross-referenced and further delineated to the actual work that needs to be completed. A Work Breakdown Structure (or WBS), is the method of time-phasing the work using detailed tasks that integrate scope, cost, and schedule at the lowest level of achievement.

Baselining and Performance Management – are essential for project control in this environment. In this case, project and program schedule, cost, and resources are (ideally) risk adjusted and a performance management baseline is established: the basis for the assessment and control of the project.

This leads us to the methodology that is always on the cusp of being the Ozymandias of program management: earned value management or EVM. The discipline of EVM arose out of the Space Age era of the 1960s. The premise is simple: when undertaking any complex effort there is a finite amount of money and resources, and a target date for the needed end item. We need a method to determine whether the actual work performed in terms of budgeted resources and time is tracking to the plan to produce the desired end item application.

When looking at the utility of EVM, one must ask: while each of the disciplines noted above also track achievement over the lifecycle of the project or program, do any combine an analysis against budgeted time and resources? The answer is no, and so EVM is essential to management of these efforts.

Still, our other disciplines also track important information that is not captured by EVM. Thus, the entire corpus of our disciplines represents the project and program ecosystem. These processes, procedures, and the measures derived from them are interconnected. It is this salient fact that points us in the direction regarding the future of program management.

Conclusions from Part One

Given that we have outlined the unique and distinctive characteristics of public interest program management, the environment and basis upon which such program management rests, and the highly developed disciplines that have evolved as a result of the experience in system development, deployment, and lifecycle management, our inquiry must next explore the evolutionary nature of the program organization itself. Once identified and delineated, we must then determine the place of program organization within the context of developments in systems and information theory which will give us insight into the future of program management.

Take Me to the River, Part 1, Cost Elements – A Digital Inventory of Integrated Program Management Elements

In a previous post I recommended a venue focused on program managers to define what constitutes integrated program management. Since that time I have been engaged with thought leaders and influencers in both government and industry, many of whom came to a similar conclusion independently, agree in this proposition and who are working to bring it about.

My own interest in this discussion is from the perspective of maximization of the information ecosystem that underlies and describes the systems known as projects and programs. But what do I mean by this? This is more than a gratuitous question, because oftentimes the information essential to defining project and program performance and behavior are intermixed, and therefore diluted and obfuscated, by confusion with those of the overall enterprise.

Project vs. Program

What a mean by the term project in this context is an organization that is established around a defined effort of fixed duration (a defined beginning and projected end) that is specifically planned and organized for the development and deployment of a particular end item, state, or result, with an identified set of resources assigned and allocated to achieve its goals.

A program is defined as a set of interrelated projects and sub-projects which is also of fixed duration that is specifically planned and organized not only for the development and deployment, but also the continues this role through sustainment (including configuration control), of a particular end item, state, or result, with an identified set of resources assigned and allocated to achieve its goals. As such, the program management team also is the first level life-cycle manager of the end item, state, or result, and participates with other levels of the organization in these activities. (More on life-cycle costs below).

Note the difference in scope and perspective, though oftentimes we use these terms interchangeably.

For shorthand, a small project of short duration operates at the tactical level of planning. A larger project, which because of size, complexity, duration, and risk approaches the definition of a program, operates at the operational level, as do most programs. Larger and more complex programs that will affect the core framing assumptions of the enterprise align their goals to the strategic level of planning. Thus, there are differences in scale, complexity and, hence, data points that can be captured at these various levels.

Another aspect of the question of establishing an integrated digital project and program management environment is sufficiency of data, which relates directly to scale. Sufficiency in this regard is defined as whether there is enough data to establish a valid correlation and, hopefully, draw a causation. Micro-economic foundations–and models–often fail because of insufficient data. This is important to keep in mind as we inventory the type of data available to us and its significance. Oftentimes additional data points can make up for those cases where there is insufficiency in the depth and quality of a more limited set of data points. Doing so will also mitigate subjectivity, especially in smaller efforts.

Thus, in constructing a project or program, regardless of its level of planning, we often begin by monitoring the most basic elements. These are usually described as cost, schedule, performance, and risk, though I will discuss and identify other contributors that can be indexed.

This first post will concentrate on the first set of elements–those that constitute cost. In looking at these, however, we will find that the elements within this category are a bit broader than what is currently used in determining project and program performance.

Contract Costs

When we refer to costs in project and program management we oftentimes are referring to those direct and indirect costs expended by the supplier over the course of the effort, particular in Cost Plus contractual efforts. The breakout of cost from a data perspective places it in subcategories:

Note that these are costs within the contract itself, as a cohesive, self-identifying entity. But there are other costs associated with our contracts which feed into program and project management. These are necessary to identify and capture if we are to take an holistic approach to these disciplines.

The costs that are anticipated by the contract are based on cost estimates, which need to be funded. These funded costs will be allocated to particular lines in the contract (CLINs), whether these be supporting contract efforts or deliverables. Thus, additional elements of our digital inventory include these items but lead us to our next categories.

Cost Estimates, Colors of Money, and Cash Flow

Cost estimates are the basis for determining the entire contract effort, and eventually make it into the project and program cost plan. Once cost estimates are applied and progress is tracked through the collection of actual costs, these elements are further traced to project and program activities, products, commodities, and other business categories, such as the indirect costs identified on the right hand side of the chart above.

Our cost plans need to be financed, as with any business entity. Though the most complex projects often are financed by some government entity because of their scale and impact, private industry–even among the largest companies–must obtain financing for the efforts at hand, whether these come from internal or external sources.

Thus two more elements present themselves: “colors” of money, that is, money that is provided for a specific purpose within the project and program cost plan which could also be made available for only some limited period of time, and the availability of that money sufficient to execute particular portions of the project or program, that is, cash flow.

The phase of the project or program will determine the type of money that is made available. These are also contained in the costs that are identified in the next section, but include, from a government financing perspective, Research, Development, Test and Evaluation (RDT&E) money, Procurement, Operations and Maintenance (O&M), and Military Construction (MILCON) dollars. By Congressional appropriation and authorization, each of these types of money may be provided for particular programs, and each type of authorization has a specific period in which they can be committed, obligated, and expended before they expire. The type of money provided also aligns with the phase of the project or program: whether it still be in development, production, deployment and acquisition, sustainment, or retirement.

These costs will be reflected in reporting that reflects actual and projected rates of expenditure, that will be tied to procurement, material management, and resource management systems.

Additional Relative Costs

As with all efforts, the supplier is not the only entity to incur costs on a development project or program. The customer also incurs costs, which must be taken into account in determining the total cost of the effort.

For anyone who has undergone any kind of major effort on their home, or even had to get things other workaday things done, like deciding when to change the tires on the car or when to get to the dentist implicitly understand that there is more effort in timing and determining the completion of these items than the cost of new kitchen cabinets, tires, or a filling. One must decide to take time off from work. One must look to their own cash flow to see if they have sufficient funds not only for the merchant, but for all of the sundry and associated tasks that must be done in preparation for and after the task’s completion. To choose to do one thing is to choose not to do another–an opportunity cost. Other people may be involved in the decision. Perhaps children are in the household and a babysitter is required. Perhaps the home life is so disrupted that another temporary abode is necessary on a short term basis.

All of these are costs that one must take into account, and at the individual level we do these calculations and plan these activities as a matter of fact.

In customer-supplier relationships the former incurs costs above the contract costs, which must be taken into account by the customer project or program executive. In the Department of Defense an associated element is called program management administration (PMA). For private entities this falls into allocated G&A and Overhead costs, aside from direct labor and material costs, but in all cases these are costs that have come about due to the decision to undertake the specific effort.

Other elements of cost on the customer side are contractually furnished facilities, property, material or equipment, and testing and evaluation costs.

Contract Cost Performance: Earned Value Management

I will further discuss EVM in more detail a later installment of this element inventory, but mention must be made of EVM since to exclude it is to be grossly remiss.

At core EVM is a financial measure of value against what has been physically achieved against a performance management baseline (PMB), which ties actual costs and completion of work through a work breakdown structure (WBS). It is focused on the contract level of performance, which in some cases may constitute the entire project, though not necessarily the entire effort for the program.

Linkages to the other cost elements I have delineated elsewhere in this post ranges from strong to non-existent. Thus, while an essential means of linking contractual achievement to work accomplishment that, at various levels of fidelity, is linked to actual technical achievement, it does not capture all of the costs in our data inventory.

An essential overview in understanding what it does capture is best summed up in the following diagram taken from the Defense Acquisition University (DAU) site:

Commercial EVM elements, while not necessarily using the same terminology or highly structured process, possess a similar structure in allocating costs and achievement against baseline costs in developmental efforts to work packages (oftentimes schedule tasks in resource-loaded schedules) under an integrated WBS structure with Management Reserve not included as part of the baseline.

Also note that commercial efforts often include their internal costs as part of the overall contractual effort in assessing earned value against actual work achievement, while government contracting efforts tend to exclude these inherent costs. That being said, it is not that there is no cost control in these elements, since strict ceilings often apply to PMA and other such costs, it is that contract cost performance does not take these costs, among others, into account.

Furthermore, the chart above provides us with additional sub-elements in our inventory that are essential in capturing data at the appropriate level of our project and program hierarchy.

Thus, for IPM, EVM is one of many elements that are part our digital inventory–and one that provides a linkage to other non-cost elements (WBS). But in no way should it be viewed as capturing all essential costs associated with a contractual effort, aside from the more expansive project or program effort.

Portfolio Management and Life-Cycle Costs

There is another level of management that is essential in thinking about project and program management, and that is the program executive level. In the U.S. military services these are called Program Executive Officers (PEOs). In private industry they are often product managers, CIOs, and other positions that often represent the link between the program management teams and the business operations side of the organization. Thus, this is also the level of management organized to oversee a number of individual projects and programs that are interrelated based on mission, commodity, or purpose. As such, this level of management often concentrates on issues across the portfolio of projects and programs.

The main purpose of the portfolio management level is to ensure that project and program efforts are aligned with the strategic goals of the organization, which includes an understanding of the total cost of ownership.

In performing this purpose one of the functions of portfolio management is to identify risks that may manifest within projects and programs, and to determine the most productive use of limited resources across them, since they are essentially competing for the same dollars. This includes cost estimates and re-allocations to address ontological, aleatory, and epistemic risk.

Furthermore, the portfolio level is also concerned with the life-cycle factors of the item under development, so that there is effective hand-off at the production and sustainment phases. The key here is to ensure that each project or program, which is focused on the more immediate goals of project and program execution, continues to meet the goals of the organization in terms of life-cycle costs, and its effectiveness in meeting the established goals essential to the project or program’s framing assumptions.

But here we are focusing on cost, and so the costs involved are trade-off costs and opportunities, assessments of return on investment, and the aforementioned total cost of ownership of the end item or system. The costs that contribute to the total cost of ownership include all of the development costs, external and internal program management costs, procurement costs, operations and support costs, maintenance and life extension costs, and system retirement costs.

Conclusion

I believe that the survey of cost elements presented in this initial post illustrates that present digital project and program management systems are limited and immature–capturing and evaluating only a small portion of the total amount of available data.

These gaps make it impossible, for example, to determine the relative significance any one element–and the analytics that can derived from it–over another; not to mention the inability to provide the linkage among these absent elements that would garner insights into cause-and-effect and predictive behavior so that we have enough time to influence the outcome.

It is also clear that, when we strive to define what constitutes integrated project and program management, that we must learn what is of most importance to the PM in performing those duties that are viewed as essential to success, and which are not yet captured in our analytical and predictive systems.

Only when our systems reach the level of cohesiveness and comprehensiveness in providing organizational insight and intelligence essential to project or program management will PMs ignore them at their own risk. In getting there we must first identify what can be captured from the activities that contribute to our efforts.

My next post will identify essential elements related to planning and scheduling.

 

Note: I am indebted to Defense Acquisition University’s resources in my research across many of my postings and link to them for the edification of the reader. For more insight into many of the points raised in this post I would recommend that readers familiarize themselves with A Guide for DoD Program Managers.

 

Ground Control from Major Tom — Breaking Radio Silence: New Perspectives on Project Management

Since I began this blog I have used it as a means of testing out and sharing ideas about project management, information systems, as well to cover occasional thoughts about music, the arts, and the meaning of wisdom.

My latest hiatus from writing was due to the fact that I was otherwise engaged in a different sort of writing–tech writing–and in exploring some mathematical explorations related to my chosen vocation, aside from running a business and–you know–living life.  There are only so many hours in the day.  Furthermore, when one writes over time about any one topic it seems that one tends to repeat oneself.  I needed to break that cycle so that I could concentrate on bringing something new to the table.  After all, it is not as if this blog attracts a massive audience–and purposely so.  The topics on which I write are highly specialized and the members of the community that tend to follow this blog and send comments tend to be specialized as well.  I air out thoughts here that are sometimes only vaguely conceived so that they can be further refined.

Now that that is out of the way, radio silence is ending until, well, the next contemplation or massive workload that turns into radio silence.

Over the past couple of months I’ve done quite a bit of traveling, and so have some new perspectives that and trends that I noted and would like to share, and which will be the basis (in all likelihood) of future, more in depth posts.  But here is a list that I have compiled:

a.  The time of niche analytical “tools” as acceptable solutions among forward-leaning businesses and enterprises is quickly drawing to a close.  Instead, more comprehensive solutions that integrate data across domains are taking the market and disrupting even large players that have not adapted to this new reality.  The economics are too strong to stay with the status quo.  In the past the barrier to integration of more diverse and larger sets of data was the high cost of traditional BI with its armies of data engineers and analysts providing marginal value that did not always square with the cost.  Now virtually any data can be accessed and visualized.  The best solutions, providing pre-built domain knowledge for targeted verticals, are the best and will lead and win the day.

b.  Along these same lines, apps and services designed around the bureaucratic end-of-month chart submission process are running into the new paradigm among project management leaders that this cycle is inadequate, inefficient, and ineffective.  The incentives are changing to reward actual project management in lieu of project administration.  The core fallacy of apps that provide standard charts based solely on user’s perceptions of looking at data is that they assume that the PM domain knows what it needs to see.  The new paradigm is instead to provide a range of options based on the knowledge that can be derived from data.  Thus, while the options in the new solutions provide the standard charts and reports that have always informed management, KDD (knowledge discovery in database) principles are opening up new perspectives in understanding project dynamics and behavior.

c.  Earned value is *not* the nexus of Integrated Project Management (IPM).  I’m sure many of my colleagues in the community will find this statement to be provocative, only because it is what they are thinking but have been hesitant to voice.  A big part of their hesitation is that the methodology is always under attack by those who wish to avoid accountability for program performance.  Thus, let me make a point about Earned Value Management (EVM) for clarity–it is an essential methodology in assessing project performance and the probability of meeting the constraints of the project budget.  It also contributes data essential to project predictive analytics.  What the data shows from a series of DoD studies (currently sadly unpublished), however, is that it is planning (via a Integrated Master Plan) and scheduling (via an Integrated Master Schedule) that first ties together the essential elements of the project, and will record the baking in of risk within the project.  Risk manifested in poorly tying contract requirements, technical performance measures, and milestones to the plan, and then manifested in poor execution will first be recorded in schedule (time-based) performance.  This is especially true for firms that apply resource-loading in their schedules.  By the time this risk translates and is recorded in EVM metrics, the project management team is performing risk handling and mitigation to blunt the impact on the performance management baseline (the money).  So this still raises the question: what is IPM?  I have a few ideas and will share those in other posts.

d.  Along these lines, there is a need for a Schedule (IMS) Gold Card that provides the essential basis of measurement of programmatic risk during project execution.  I am currently constructing one with collaboration and will put out a few ideas.

e.  Finally, there is still room for a lot of improvement in project management.  For all of the gurus, methodologies, consultants, body shops, and tools that are out there, according to PMI, more than a third of projects fail to meet project goals, almost half to meet budget expectations, less than half finished on time, and almost half experienced scope creep, which, I suspect, probably caused “failure” to be redefined and under-reported in their figures.  The assessment for IT projects is also consistent with this report, with CIO.com reporting that more than half of IT projects fail in terms of meeting performance, cost, and schedule goals.  From my own experience and those of my colleagues, the need to solve the standard 20-30% slippage in schedule and similar overrun in costs is an old refrain.  So too is the frustration that it need take 23 years to deploy a new aircraft.  A .5 CPI and SPI (to use EVM terminology) is not an indicator of success.  What this indicates, instead, is that there need to be some adjustments and improvements in how we do business.  The first would be to adjust incentives to encourage and reward the identification of risk in project performance.  The second is to deploy solutions that effectively access and provide information to the project team that enable them to address risk.  As with all of the points noted in this post, I have some other ideas in this area that I will share in future posts.

Onward and upward.

Technical Foul — It’s Time for TPI in EVM

For more than 40 years the discipline of earned value management (EVM) has gone through a number of changes in its descriptions, governance, and procedures.  During that same time its community has been resistant to improvements in its methodology or to changes that extend its value when taking into account other methods that either augment its usefulness, or that potentially provide more utility in the area of performance management.  This has been especially the case where it is suggested that EVM is just one of many methodologies that contribute to this assessment under a more holistic approach.

Instead, it has been asserted that EVM is the basis for integrated project management.  (I disagree–and solely on the evidence that if it was so, then project managers would more fully participate in its organizations and conferences.  This would then pose the problem that PMs might then propose changes to EVM that, well…default to the second sentence in this post).  As evidence it need only be mentioned that there has been resistance to such recent developments in using earned schedule, technical performance, and risk–most especially risk based on Bayesian analysis).

Some of this resistance is understandable.  First, it took quite a long time just to get to a consensus on the application of EVM, though its principles and methods are based on simple and well proven statistical methods.  Second, the industries in which EVM has been accepted are sensitive to risk, and so a bureaucracy of practitioners have grown to ensure both consensus and compliance to accepted methods.  Third, the community that makes up practitioners of EVM consist mostly of cost analysts, trained in simple accounting, arithmetic, and statistical methodology.  It is thus a normal human bias to assume that the path of one’s previous success is the way to future success, though our understanding of the design space (reality) that we inhabit has been enhanced through new knowledge.  Fourth, there is a lot of data that applies to project management, and the EVM community is only now learning of the ways that this other data impacts our understanding of measuring project performance and the probability of reaching project goals in rolling out a product.  Finally, there is the less defensible reason that a lot of people and firms have built their careers that depends on maintaining the status quo.

Our ability to integrate disparate datasets is accelerating on a yearly basis thanks to digital technology, and the day in achieving integration of all relevant factors in project and enterprise performance is inevitable.  To be frank, I am personally engaged in such projects and am assisting organizations in moving in this direction today.  Regardless, we can make an advance in the discipline of performance management by pulling down low hanging fruit.  The most reachable one, in my opinion, is technical performance measurement.

The literature of technical performance has come quite a long way, thanks largely to the work of the Institute for Defense Analyses (IDA) and others, particularly the National Defense Industrial Association through the publication of their predictive measures guide.  This has been a topic of interest to me since its study was part of my duties back when I was still wearing a uniform.  The early results of these studies resulted in a paper that proposed a method of integrating technical performance, earned value, and risk.  A pretty comprehensive overview of the literature and guidance for technical performance can be found at this presentation by Glen Alleman and Tom Coonce given at EVM World in 2015.  It must be mentioned that Rick Price of Lockheed Martin also contributed greatly to this literature.

Keep in mind what is meant when we decide to assess technical performance within the context of R&D.  It is an assessment against expected or specified:

a.  Measures of Effectiveness (MoE)

b.  Measures of Performance (MoP), and

c.  Key Performance Parameters (KPP)

The opposition from the project management community to widespread application of this methodology took two forms.  First, it was argued, the method used to adjust the value of earned (CPI) seemed always to have a negative impact.  Second, there are technical performance factors that transcend the WBS, and so it is hard to properly adjust the individual control accounts based on the contribution of technical performance.  Third, some performance measures defy an assessment of value in a time-phased manner.  The most common example has been tracking weight of aircraft, which has contributors from virtually all components that go into it.

Let’s take these in order.  But lest one think that this perspective is an artifact from 1997, just a short while ago, in the A&D community, the EVM policy office at DoD attempted to apply a somewhat modest proposal of ensuring that technical performance was included as an element in EVM reporting.  Note that the EIA 748 standard states this clearly and has done so for quite some time.  Regardless, the same three core objections were raised in comments from the industry.  Thus, this caused me to ask some further in-depth questions and my revised perspective follows below.

The first condition occurred, in many cases, due to optimism bias in registering earned value, which often occurs when using a single point estimate of percent complete by a limited population of experts contributing to an assessment of the element.  Fair enough, but as you can imagine, its not a message that a PM wants to hear or will necessarily accept or admit, regardless of the merits.  There are more than enough pathways to second guessing and testing selection bias at other levels of reporting.  Glen Alleman in his Herding Cats blog post of 12 August has a very good post listing the systemic reasons for program failure.

Another factor is that the initial methodology did possess a skewing toward more pessimistic results.  This was not entirely apparent at the time because the statistical methods applied did not make that clear.  But, to critique that first proposal, which was the result of contributions from IDA and other systems engineering technical experts, the 10-50-90 method in assessing probability along the bandwidth of the technical performance baseline was too inflexible.  The graphic that we proposed is as follows and one can see that, while it was “good enough”, if rolled up there could be some bias that required adjustment.

TPM Graphic

 

Note that this range around 50% can be interpreted to be equivalent to the bandwidth found in the presentation given by Alleman and Coonce (as well as the Predictive Measures Guide), though the intent here was to perform an assessment based on a simplified means of handicapping the handicappers–or more accurately, performing a probabilistic assessment on expert opinion.  The method of performing Bayesian analysis to achieve this had not yet matured for such applications, and so we proposed a method that would provide a simple method that our practitioners could understand that still met the criteria of being a valid approach.  The reason for the difference in the graphic resides in the fact that the original assessment did not view this time-phasing as a continuous process, but rather an assessment at critical points along the technical baseline.

From a practical perspective, however, the banding proposed by Alleman and Coonce take into account the noise that will be experienced during the life cycle of development, and so solves the slight skewing toward pessimism.  We’ll leave aside for the moment how we determine the bands and, thus, acceptable noise as we track along our technical baseline.

The second objection is valid only so far as any alignment of work-related indicators vary from project to project.  For example, some legs of the WBS tree go down nine levels and others go down five levels, based on the complexity of the work and the organizational breakdown structure (OBS).  Thus where we peg within each leg of the tree the control account (CA) and work package (WP) level becomes relative.  Do the schedule activities have a one-to-one relationship or many-to-one relationship with the WP level in all legs?  Or is the lowest level that the alignment can be made in certain legs at the CA level?

Given that planning begins with the contract spec and (ideally) proceed from IMP –> IMS –> WBS –> PMB in a continuity, then we will be able to determine the contributions of TPM to each WBS element at their appropriate level.

This then leads us to another objection, which is that not all organizations bother with developing an IMP.  That is a topic for another day, but whether such an artifact is created formally or not, one must achieve in practice the purpose of the IMP in order to get from contract spec to IMS under a sufficiently complex effort to warrant CPM scheduling and EVM.

The third objection is really a child of the second objection.  There very well may be TPMs, such as weight, with so many contributors that distributing the impact would both dilute the visibility of the TPM and present a level of arbitrariness in distribution that would render its tracking useless.  (Note that I am not saying that the impact cannot be distributed because, given modern software applications, this can easily be done in an automated fashion after configuration.  My concern is in regard to visibility on a TPM that could render the program a failure).  In these cases, as with other indicators that must be tracked, there will be high level programmatic or contract level TPMs.

So where do we go from here?  Alleman and Coonce suggest adjusting the formula for BCWP, where P is informed by technical risk.  The predictive measures guide takes a similar approach and emphasizes the systems engineering (SE) domain in getting to an assessment to determine the impact of reported EVM element performance.  The recommendation of the 1997 project that I headed in assignments across Navy and OSD, was to inform performance based on a risk assessment of probable achievement at each discrete performance milestone.  What all of these studies have in common, and in common with common industry practice using SE principles, is an intermediate assessment, informed by risk, of a technical performance index against a technical performance baseline.

So let’s explore this part of the equation more fully.

Given that we have MoE, MoP, and KPP are identified for the project, different methods of determining progress apply.  This can be a very simplistic set of TPMs that, through the acquisition or fabrication of compliant materials, meet contractual requirements.  These are contract level TPMs.  Depending on contract type, achievement of these KPPs may result in either financial penalties or financial reward.  Then there are the R&D-dependent MoEs, MoPs, and KPPs that require more discrete time-phasing and ties to the physical completion of work documented by through the WBS structure.  As with EVM on the measurement of the value of work, our index of physical technical achievement can be determined through various methods: current EVM methods, simulated Monte Carlo technical risk, 10-50-90 risk assessment, Bayesian analysis, etc.  All of these methods are designed to militate against selection bias and the inherent limitations of limited sample size and, hence, extreme subjectivity.  Still, expert opinion is a valid method of assessment and (in cases where it works) better than a WAG or coin flip.

Taken together these TPMs can be used to determine the technical achievement of the project or program over time, with a financial assessment of the future work needed to bring it in line.  These elements can be weighted, as suggested by Coonce, Alleman, and Price, through an assessment of relative risk to project success.  Some of these TPIs will apply to particular WBS elements at various levels (since their efforts are tied to specific activities and schedules via the IMS), and the most important project and program-level TPMs are reflected at that level.

What about double counting?  A comparison of the aggregate TPIs and the aggregate CPI and SPI will determine the fidelity of the WBS to technical achievement.  Furthermore, a proper baseline review will ensure that double counting doesn’t occur.  If the element can be accounted for within the reported EVM elements, then it need not be tracked separately by a TPI.  Only those TPMs that cannot be distributed or that represent such overarching risk to project success need be tracked separately, with an overall project assessment made against MR or any reprogramming budget available that can bring the project back into spec.

My last post on project management concerned the practices at what was called Google X.  There incentives are given to teams that identify an unacceptably high level of technical risk that will fail to pay off within the anticipated planning horizon.  If the A&D and DoD community is to become more nimble in R&D, it needs the necessary tools to apply such long established concepts such as Cost-As-An-Independent-Variable (CAIV), and Agile methods (without falling into the bottomless pit of unsupported assertions by the cult such as elimination of estimating and performance tracking).

Even with EVM, the project and program management community needs a feel for where their major programmatic efforts are in terms of delivery and deployment, in looking at the entire logistics and life cycle system.  The TPI can be the logic check of whether to push ahead, or finishing the low risk items that are remaining in R&D to move to first item delivery, or to take the lessons learned from the effort, terminate the project, and incorporate those elements into the next generation project or related components or systems.  This aligns with the concept of project alignment with framing assumptions as an early indicator of continued project investment at the corporate level.

No doubt, existing information systems, many built using 1990s technology and limited to line-and-staff functionality, do not provide the ability to do this today.  Of course, these same systems do not take into account a whole plethora of essential information regarding contract and financial management: from the tracking of CLINs/SLINs, to work authorization and change order processing, to the flow of funding from TAB to PMB/MR and from PMB to CA/UB/PP, contract incentive threshold planning, and the list can go on.  What this argues for is innovation and rewarding those technology solutions that take a more holistic approach to project management within its domain as a subset of program, contract, and corporate management–and such solutions that do so without some esoteric promise of results at some point in the future after millions of dollars of consulting, design, and coding.  The first company or organization that does this will reap the rewards of doing so.

Furthermore, visibility equals action.  Diluting essential TPMs within an overarching set of performance metrics may have the effect of hiding them and failing to properly identify, classify, and handle risk.  Including TPI as an element at the appropriate level will provide necessary visibility to get to the meat of those elements that directly impact programmatic framing assumptions.

River Deep, Mountain High — A Matrix of Project Data

Been attending conferences and meetings of late and came upon a discussion of the means of reducing data streams while leveraging Moore’s Law to provide more, better data.  During a discussion with colleagues over lunch they asked if asking for more detailed data would provide greater insight.  This led to a discussion of the qualitative differences in data depending on what information is being sought.  My response to more detailed data was to respond: “well there has to be a pony in there somewhere.”  This was greeted by laughter, but then I finished the point: more detailed data doesn’t necessarily yield greater insight (though it could and only actually looking at it will tell you that, particularly in applying the principle of KDD).  But more detailed data that is based on a hierarchical structure will, at the least, provide greater reliability and pinpoint areas of intersection to detect areas of risk manifestation that is otherwise averaged out–and therefore hidden–at the summary levels.

Not to steal the thunder of new studies that are due out in the area of data later this spring but, for example, I am aware after having actually achieved lowest level integration for extremely complex projects through my day job, that there is little (though not zero) insight gained in predictive power between say, the control account level of a WBS and the work package level.  Going further down to element of cost may, in the words of the character in the movie Still Alice, where “You may say that this falls into the great academic tradition of knowing more and more about less and less until we know everything about nothing.”  But while that may be true for project management, that isn’t necessarily so when collecting parametrics and auditing the validity of financial information.

Rolling up data from individually detailed elements of a hierarchy is the proper way to ensure credibility.  Since we are at the point where a TB of data has virtually the same marginal cost of a GB of data (which is vanishingly small to begin with), then the more the merrier in eliminating the abuse associated with human-readable summary reporting.  Furthermore, I have long proposed through this blog and elsewhere, that the emphasis should be away from people, process, and tools, to people, process, and data.  This rightly establishes the feedback loop necessary for proper development and project management.  More importantly, the same data available through project management processes satisfy the different purposes of domains both within the organization, and of multiple external stakeholders.

This then leads us to the concept of integrated project management (IPM), which has become little more than a buzz-phrase, and receives a lot of hand waves, mostly by technology companies that want to push their tools–which are quickly becoming obsolete–while appearing forward leaning.  This tool-centric approach is nothing more than marketing–focusing on what the software manufacturer would have us believe is important based on the functionality baked into their applications.  One can see where this could be a successful approach, given the emphasis on tools in the PM triad.  But, of course, it is self-limiting in a self-interested sort of way.  The emphasis needs to be on the qualitative and informative attributes of available data–not of tool functionality–that meet the requirements of different data consumers while minimizing, to the extent possible, the number of data streams.

Thus, there are at least two main aspects of data that are important in understanding the utility of project management: early warning/predictiveness and credibility/traceability/fidelity.  The chart attached below gives a rough back-of-the-envelope outline of this point, with some proposed elements, though this list is not intended to be exhaustive.

PM Data Matrix

PM Data Matrix

In order to capture data across the essential elements of project management, our data must demonstrate both a breadth and depth that allows for the discovery of intersections of the different elements.  The weakness in the two-dimensional model above is that it treats each indicator by itself.  But, when we combine, for example, IMS consecutive slips with other elements listed, the informational power of the data becomes many times greater.  This tells us that the weakness in our present systems is that we treat the data as a continuity between autonomous elements.  But we know that the project consists of discontinuities where the next level of achievement/progress is a function of risk.  Thus, when we talk about IPM, the secret is in focusing on data that informs us what our systems are doing.  This will require more sophisticated types of modeling.

The Song Remains the Same (But the Paradigm Is Shifting) — Data Driven Assessment and Better Software in Project Management

Probably the biggest news out of the NDIA IPMD meeting this past week was the unofficial announcement by Frank Kendall, who is the Undersecretary of Defense for Acquisition, Technology, and Logistics USD(AT&L), that thresholds would be raised for mandatory detailed surveillance of programs to $100M from the present requirement of $20M.  While earned value management implementation and reporting will still be required on programs based on dollar value, risk, and other key factors, especially the $20M threshold for R&D-type projects, the raising of the threshold for mandatory surveillance reviews was seen as good news all around for reducing some regulatory burden.  The big proviso in this announcement, however, was that it is to go into effect later this summer and that, if the data in reporting submissions show inconsistencies and other anomalies that call into question the validity of performance management data, then all bets are off and the surveillance regime is once again imposed, though by exception.

The Department of Defense–especially under the leadership of SecDef Ashton Carter and Mr. Kendall–has been looking for ways of providing more flexibility in acquisition to allow for new technology to be more easily leveraged into long-term, complex projects.  This is known as the Better Buying Power 3.0 Initiative.  It is true that surveillance and oversight can be restrictive to the point of inhibiting industry from concentrating on the business of handling risk in project management, causing resources to be devoted to procedural and regulatory issues that do not directly impact whether the project will successfully achieve its goals within a reasonable range of cost and schedule targets.  Furthermore, the enforcement of surveillance has oftentimes been inconsistent and–in the worst cases–contrary to the government’s own guidance due to inconsistent expertise and training.  The change maintains a rigorous regulatory environment for the most expensive and highest risk projects, while reducing unnecessary overhead, and allowing for more process flexibility for those below the threshold, given that industry’s best practices are effective in exercising project control.

So the question that lay beneath the discussion of the new policy coming out of the meeting was: why now?  The answer is that technology has reached the point where the ability to effectively use the kind of Big Data required by DoD and other large organizations to detect patterns in data that suggest systems issues has changed both the regulatory and procedural landscape.

For many years as a techie I have heard the mantra that software is a nice reporting and analysis tool (usually looking in the rear view mirror), but that only good systems and procedures will ensure a credible and valid system.  This mantra has withstood the fact that projects have failed at the usual rate despite having the expected artifacts that define an acceptable project management system.  Project organizations’ systems descriptions have been found to be acceptable, work authorization, change control, and control account plans, PMBs, and IMSs have all passed muster and yet projects still fail, oftentimes with little advance warning of the fatal event or series of events.  More galling, the same consultants and EVM “experts” can be found across organizations without changing the arithmetic of project failure.

It is true that there are specific causes for this failure: the inability of project leadership to note changes in framing assumptions, the inability of our systems and procedures to incorporate technical performance into overall indicators of project performance, and the inability of organizations to implement and enforce their own policies.  But in the last case, it is not clear that the failure to follow controls in all cases had any direct impact on the final result; they were contributors to the failure but not the main cause.  It is also true that successful projects have experienced many of the same discrepancies in their systems and procedures.  This is a good indication that something else is afoot: that there are factors not being registered when we note project performance, that we have a issue in defining “done”.

The time has come for systems and procedural assessment to step aside as the main focus of compliance and oversight.  It is not that systems and procedures are unimportant.  It is that data driver assessment–and only data driver assessment–that is powerful enough to quickly and effectively identify issues within projects that otherwise go unreported.  For example, if we call detailed data from the performance management systems that track project elements of cost, the roll up should, theoretically, match the summarized data at the reporting level.  But this is not always the case.

There are two responses to this condition.  The first is: if the variations are small; that is, within 1% or 2% from the actuals, we must realize that earned value management is a project management system, not a financial management systems, and need not be exact.  This is a strong and valid assertion.  The second, is that the proprietary systems used for reporting have inherent deficiencies in summarizing reporting.  Should the differences once again not be significant, then this too is a valid assertion.  But there is a point at which these assertions fail.  If the variations from the rollups is more significant than (I would suggest) about 2% from the rollup, then there is a systemic issue with the validity of data that undermines the credibility of the project management systems.

Checking off compliance of the EIA 748 criteria will not address such discrepancies, but a robust software solution that has the ability to handle such big data, the analytics to identify such discrepancies, and the flexibility to identify patterns and markers in the data that suggest an early indication of project risk manifestation will address the problem at hand.  The technology is now here to be able to perform this operation and to do so at the level of performance expected in desktop operations.  This type of solution goes far beyond EVM Tools or EVM engines.  The present generation of software possesses both the ability to hardcode solutions out of the box, but also the ability to configure objects, conditional formatting, calculations, and reporting from the same data to introduce leading indicators across a wider array of project management dimensions aside from just cost and schedule.

 

Days of Future Passed — Legacy Data and Project Parametrics

I’ve had a lot of discussions lately on data normalization, including being asked the question of what constitutes normalization when dealing with legacy data, specifically in the field of project management.  A good primer can be found at About.com, but there are also very good older papers out on the web from various university IS departments.  The basic principals of data normalization today consist of finding a common location in the database for each value, reducing redundancy, properly establishing relationships among the data elements, and providing flexibility so that the data can be properly retrieved and further processed into intelligence in such as way as the objects produced possess significance.

The reason why answering this question is so important is because our legacy data is of such a size and of such complexity that it falls into the broad category of Big Data.  The condition of the data itself provides wide variations in terms of quality and completeness.  Without understanding the context, interrelationships, and significance of the elements of the data, the empirical approach to project management is threatened, since being able to use this data for purposes of establishing trends and parametric analysis is limited.

A good paper that deals with this issue was authored by Alleman and Coonce, though it was limited to Earned Value Management (EVM).  I would argue that EVM, especially in the types of industries in which the discipline is used, is pretty well structured already.  The challenge is in the other areas that are probably of more significance in getting a fuller understanding of what is happening in the project.  These areas of schedule, risk, and technical performance measures.

In looking at the Big Data that has been normalized to date–and I have participated with others in putting a significant dent in this area–it is apparent that processes in these other areas lack discipline, consistency, completeness, and veracity.  By normalizing data in sub-specialties that have experienced an erosion in enforcing standards of quality and consistency, technology becomes a driver for process improvement.

A greybeard in IT project management once said to me (and I am not long in joining that category): “Data is like water, the more it flows downstream the cleaner it becomes.”  What he meant is that the more that data is exposed in the organizational stream, the more it is questioned and becomes a part of our closed feedback loop: constantly being queried, verified, utilized in decision making, and validated against reality.  Over time more sophisticated and reliable statistical methods can be applied to the data, especially if we are talking about performance data of one sort or another, that takes periodic volatility into account in trending and provides us with a means for ensuring credibility in using the data.

In my last post on Four Trends in Project Management, I posited that the question wasn’t more or less data but utilization of data in a more effective manner, and identifying what is significant and therefore “better” data.  I recently heard this line repeated back to me as a means of arguing against providing data.  This conclusion was a misreading of what I was proposing.  One level of reporting data in today’s environment is no more work than reporting on any other particular level of a project hierarchy.  So cost is no longer a valid point for objecting to data submission (unless, of course, the one taking that position must admit to the deficiencies in their IT systems or the unreliability of their data).

Our projects must be measured against the framing assumptions in which they were first formed, as well as the established measures of effectiveness, measures of performance, and measures of technical achievement.  In order to view these factors one must have access to data originating from a variety of artifacts: the Integrated Master Schedule, the Schedule and Cost Risk Analysis, and the systems engineering/technical performance plan.  I would propose that project financial execution metrics are also essential in getting a complete, integrated, view of our projects.

There may be other supplemental data that is necessary as well.  For example, the NDIA Integrated Program Management Division has a proposed revision to what is known as the Integrated Baseline Review (IBR).  For the uninitiated, this is a process in which both the supplier and government customer project teams can come together, review the essential project artifacts that underlie project planning and execution, and gain a full understanding of the project baseline.  The reporting systems that identify the data that is to be reported against the baseline are identified and verified at this review.  But there are also artifacts submitted here that contain data that is relevant to the project and worthy of continuing assessment, precluding manual assessments and reviews down the line.

We don’t yet know the answer to these data issues and won’t until all of the data is normalized and analyzed.  Then the wheat from the chaff can be separated and a more precise set of data be identified for submittal, normalized and placed in an analytical framework to give us more precise information that is timely so that project stakeholders can make decisions in handling any risks that manifest themselves during the window that they can be handled (or make the determination that they cannot be handled).  As the farmer says in the Chinese proverb:  “We shall see.”

No Bucks, No Buck Rogers — Project Work Authorizations, Change Control, and Cash Flow

As I’ve written here most recently, the most significant proposal coming out of the Integrated Program Management Conference (IPMC) this year was the comprehensive manner of integrating all essential elements of a project, presented by Glen Alleman et al.  In their presentation, Alleman, Coonce, and Price, present a process flow (which, in my estimation, should be mirrored in data and information flow) in which program artifacts were imbued with measures of effectiveness, measures of performance, and measures of progress, to achieve an organic integration of all parts of the project that allow the project team to make a valid assessment of achievement against the plan, informed by risk and opportunity.  (Emphasis my own).  The three-legged stool of cost, schedule, and technical performance are thereby integrated properly at the appropriate level of the project structure, and done in such a way as to overcome the rigidity and fallacy of the single point estimate.

But, as is always the case with elegant models, while they replicate a sufficient portion of reality to allow us to make our assessments using statistical methods, there are other elements that we have purposely left out because our present models do not incorporate them into the normal and normative process.  They are considered situational, and so lie just outside of the process flow, though they insert themselves when necessary–and much more frequently than desired.  I am referring to the availability of money and resources, and the manner in which they affect the project: through work authorizations (WADs) and baseline change requests (BCRs).

I have seen situations where fully 90% of the effort in project management is devoted to manage and adjust the plan based on baseline changes.  This is particularly the case where estimates are poorly developed due to the excuse of uncertainty.  Of course there is uncertainty–that’s the purpose of developing a plan.  The issue isn’t the presence of risk (and opportunity) but that our risks are educated ones, that is, informed by familiarity with similar efforts, engineering assessment, core competency, and other empirical factors.  This is where the most radical elements of the Agile Cult gets it wrong–in focusing on risk and assuming that the only way to realize opportunity is to forgo the empirical process.  This is not only a misreading of risk and opportunity assessment in project management, it is a sort of neo-Luddite position regarding scientific management.

The environment in which a project operates undergoes change.  The framing assumptions of the project determine the expectations of scope, cost, and what defines success.  The concept of framing assumptions was fully developed in a RAND study that I covered in a previous blog post.  Most often, but not always, the change in framing assumptions is reflected in the WAD and BCR process, most often in the latter.  Thus, we have a means of determining and taking account of changes in framing assumptions.  This is in the normal process of project management, as opposed to the more obvious examples of a complete replan or over target baseline (OTB).

So where do we track WADs and BCRs in our processes that will provide us sufficient indicators in our measures of effectiveness, performance, and progress that our resources (both size and type) many not be sufficient or that these changes are sufficient enough that our framing assumptions have changed?  I would argue that the linkage for resources must also be made through the Integrated Master Plan (IMP) and reflect in the IMS, cross-referenced to the PMB.  Technology can provide the remainder of the ability to integrate these elements and provide the process flow necessary to provide early warning.  This integration goes beyond the traditional focus on cost and schedule (and the newly reintroduced emphasis on technical achievement).  It involves integration with resource management systems (personnel, skillset assignments, etc.) as well as financial management systems to determine the availability of money (both its sufficiency and “color”*) being applied to the right place at the right time.

Integrating these elements together then allows for more sophisticated methods of determining project success through the introduction of metrics that provide correlations between the elements.  It also answers, absent politics, the optimum level of both analysis and reporting.

*The “color” of money applies mostly to public investments in which monies appropriated are designed by their purpose:  operations, maintenance, engineering, R&D, etc.

Note: This post was modified to add a point of clarification in applying WADs and BCRs to the PMB.

Ace of Base(line) — A New Paper on Building a Credible PMB

Glen Alleman, a leading consultant in program management (who also has a blog that I follow), Tom Coonce of the Institute for Defense Analyses, and Rick Price of Lockheed Martin, have jointly published a new paper in the College of Performance Management’s Measureable News entitled “Building A Credible Performance Measurement Baseline.”

The elements of their proposal for constructing a credible PMB, from my initial reading, are as follows:

1.  Rather than a statement of requirements, decision-makers should first conduct a capabilities gap analysis to determine the units of effectiveness and performance.  This ensures that program management decision-makers have a good idea of what “done” looks like, and ensures that performance measurements aren’t disconnected from these essential elements of programmatic success.

2.  Following from item 1 above, the technical plan and the programmatic plan should always be in sync.

3.  Earned value management is but one of many methods for assessing programmatic performance in its present state.  At least that is how I interpret what the are saying, because later in their paper they propose a way to ensure that EVM does not stray from the elements that define technical achievement.  But EVM in itself is not the end-all or be-all of performance management–and fails in many ways to anticipate where the technical and programmatic plans diverge.

4.  All work in achieving the elements of effectiveness and performance are first constructed and given structure in the WBS.  Thus, the WBS ties together all elements of the project plan.  In addition, technical and programmatic risk must be assessed at this stage, rather than further down the line after the IMS has been constructed.

5.  The Integrated Master Plan (IMP) is constructed to incorporate the high level work plans that are manifested through major programmatic events and milestones.  It is through the IMP that EVM is then connected to technical performance measures that affect the assessment of work package completion that will be reflected in the detailed Integrated Master Schedule (IMS).  This establishes not only the importance of the IMP in ensuring the linkage of technical and programmatic plans, but also makes the IMP an essential artifact that has all too often be seen as optional, which probably explains why so many project managers are “surprised” when they construct aircraft that can’t land on the deck of a carrier or satellites that can’t communicate in orbit, though they are well within the tolerance bands of cost and schedule variances.

6.  Construct the IMS taking into account the technical, qualitative, and quantitative risks associated with the events and milestones identified in the IMP.  Construct risk mitigation/handling where possible and set aside both cost and schedule margins for irreducible uncertainties, and management reserve (MR) for reducible risks, keeping in mind that margin is within the PMB but MR is above the PMB but within the CBB.  Furthermore, schedule margin should be transitioned from a deterministic one to a probabilistic one–constructing sufficient margin to protect essential activities.  Cost margin in work packages should also be constructed in the same manner-based on probabilistic models that determine the chances of making a risk reducible until reaching the point of irreducibility.  Once again, all of these elements tie back to the WBS.

7.  Cost and schedule margin are not the same as slack or float.  Margin is reserve.  Slack or float is equivalent to overruns and underruns.  The issue here in practice is going to be to get the oversight agencies to leave margin alone.  All too often this is viewed as “free” money to be harvested.

8.  Cost, schedule, and technical performance measurement, tied together at the elemental level of work–informing each other as a cohesive set of indicators that are interrelated–and tied back to the WBS, is the only valid method of ensuring accurate project performance measurement and the basis for programmatic success.

Most interestingly, in conclusion the authors present as a simplified case an historical example how their method proves itself out as both a common sense and completely reasonable approach, by using the Wright brothers’ proof of concept for the U.S. Army in 1908.  The historical documents in that case show that the Army had constructed elements of effectiveness and performance in determining whether they would purchase an airplane from brothers.  All measures of project success and failure would be assessed against those elements–which combined cost, schedule, and technical achievement.  I was particularly intrigued that the issue of weight of the aircraft was part of the assessment–a common point of argument from critics of the use of technical performance–where it is demonstrated in the paper how the Wright brothers actually assessed and mitigated the risk associated with that measure of performance over time.

My initial impression of the paper is that it is a significant step forward in bringing together all of the practical lessons learned from both the successes and failures of project performance.  Their recommendations are a welcome panacea to many of the deficiencies implicit in our project management systems and procedures.

I also believe that as an integral part of the process in construction of the project artifacts, that it is a superior approach than the one that I initially proposed in 1997, which assumed that TPM would always be applied as an additional process that would inform cost and schedule at the end of each assessment period.  I look forward to hearing the presentation at the next Integrated Program Management Conference, at which I will attempt some live blogging.

More on Excel…the contributing factor of poor Project Management apps

Some early comments via e-mails on my post on why Excel is not a PM tool raised the issue that I was being way too hard on IT shops and letting application providers off the hook.  The asymmetry was certainly not the intention (at least not consciously).

When approaching an organization seeking process and technology improvement, oftentimes the condition of using Excel is what we in the technology/PM industry conveniently call “workarounds.”  Ostensibly these workarounds are temporary measures to address a strategic or intrinsic organizational need that will eventually be addressed by a more cohesive software solution.  In all too many cases, however, the workaround turns out to be semi-permanent.

A case in point in basic project management concerns Work Authorizations Documents (WADs) and Baseline Change Requests (BCRs).  Throughout entire industries who use the most advanced scheduling applications, resource management applications, and–where necessary–earned value “engines,” the modus operandi to address WADs and BCRs is to either use Excel or to write a custom app in FoxPro or using Access.  This is fine as a “workaround” as long as you remember to set up the systems and procedures necessary to keep the logs updated, and then have in place a procedure to update the systems of record appropriately.  Needless to say, errors do creep in and in very dynamic environments it is difficult to ensure that these systems are in alignment, and so a labor-intensive feedback system must also be introduced.

This is the type of issue that software technology was designed to solve.  Instead, software has fenced off the “hard’ operations so that digitized manual solutions, oftentimes hidden from plain view from the team by the physical technological constraint of the computer (PC, laptop, etc.), are used.  This is barely a step above what we did before the introduction of digitization:  post the project plan, milestone achievements, and performance on a VIDS/MAF board that surrounded the PM control office, which ensured that every member of the team could see the role and progress of the project.  Under that system no one hoarded information, it militated against single points of failure, and ensured that disconnects were immediately addressed since visibility ensured accountability.

In many ways we have lost the ability to recreate the PM control office in digitized form.  Part of the reason resides in the 20th century organization of development and production into divisions of labor.  In project management, the specialization of disciplines organized themselves around particular functions: estimating and planning, schedule management, cost management, risk management, resource management, logistics, systems engineering, operational requirements, and financial management, among others.  Software was developed to address each of these areas with clear lines of demarcation drawn that approximated the points of separation among the disciplines.  What the software manufacturers forgot (or never knew) was that the PMO is the organizing entity and it is an interdisciplinary team.

To return to our example: WADs and BCRs; a survey of the leading planning and scheduling applications shows that while their marketing literature addresses baselines and baseline changes (and not all of them address even this basic function), they still do not understand complex project management.  There is a difference between resources assigned to a time-phased network schedule and the resources planned against technical achievement related to the work breakdown structure (WBS).  Given proper integration they should align.  In most cases they do not.  This is why most scheduling application manufacturers who claim to measure earned value, do not.  Their models assume that the expended resources align with the plan to date, in lieu of volume-based measurement.  Further, eventually understanding this concept does not produce a digitized solution, since an understanding of the other specific elements of program control is necessary.

For example, projects are initiated either through internal work authorizations in response to a market need, or based on the requirements of a contract.  Depending on the mix of competencies required to perform the work financial elements such as labor rates, overhead, G&A, allowable margin (depending on contract type), etc. will apply–what is euphemistically called “complex rates.”  An organization may need to manage multiple rate sets based on the types of efforts undertaken, with a many-to-many relationship between rate sets and projects/subprojects.

Once again, the task of establishing the proper relationships at the appropriate level is necessary.  This will then affect the timing of WAD initiation, and will have a direct bearing on the BCR approval process, given that it is heavily influenced by “what-if?” analysis against resource, labor, and financial availability and accountability (a complicated process in itself).  Thus the schedule network is not the only element affected, nor the overarching one, given the assessed impact on cost, technical achievement, and qualitative external risk.

These are but two examples of sub-optimization due to deficiencies in project management applications.  The response–and in my opinion a lazy one (or one based on the fact that oftentimes software companies know nothing of their customers’ operations)–has been to develop the alternative euphemism for “workaround”: best of breed.  Oftentimes this is simply a means of collecting revenue for a function that is missing from the core application.  It is the software equivalent of division of labor: each piece of software performs functions relating to specific disciplines and where there are gaps these are filled by niche solutions or Excel.  What this approach does not do is meet the requirements of the PMO control office, since it perpetuates application “swim lanes,” with the multidisciplinary requirements of project management relegated to manual interfaces and application data reconciliation.  It also pushes–and therefore magnifies–risk at the senior level of the project management team, effectively defeating organizational fail safes designed to reduce risk through, among other methods, delegation of responsibility to technical teams, and project planning and execution constructed around short duration/work-focused activities.  It also reduces productivity, information credibility, and unnecessarily increases cost–the exact opposite of the rationale used for investing in software technology.

It is time for this practice to end.  Technologies exist today to remove application “swim lanes” and address the multidisciplinary needs of successful project management.  Excel isn’t the answer; cross-application data access, proper data integration, and data processing into user-directed intelligence, properly aggregated and distributed based on role and optimum need to know, is.