Part three of this series of articles on the elements of Integrated Program and Project Management will focus on two additional areas of IPM: technical performance and risk management. Prior to jumping in, however–and given the timeframe over which I’ve written this series–a summary to date is in order.
The first part of our exploration into IPM digital inventory concerned cost elements. Cost in this sense was broadly defined as any cost elements that need to be of interest to a project or program managers and their teams. I first clarified our terms by defining the differences between project and program management–and how those differences will influence our focus. Then I outlined the term cost as falling into the following categories:
- Contract costs and the cost categories within the organizational hierarchy;
- Cost estimates, “colors” of money where such distinctions exist, and cashflow;
- Additional costs that relate to the program or project effort that are not always directly attributed to the effort, such as PMA, furnished materials or labor, corollary and supporting efforts on the part of the customer, and other overhead and G&A type costs;
- Contract cost performance under earned value management (EVM); and
- Portfolio management considerations and total cost of ownership.
The second part of this exposition concerned schedule elements, that is, time-phased planning and performance that is essential to any project or program effort. The article first discussed the primacy of the schedule in project and program planning and execution, given its ties in defining the basis for the cost elements addressed in the first part of the series. I then discussed the need for integrated planning as the basis for a valid executable schedule and PMB, the detailed elements and citations of the sources of that information in the literature and formal guidance, the role of framing assumptions in the construction of schedule and cost plans with its holistic approach to go/no-go decision-making, and, finally, the role of the schedule in establishing the project and program battle rhythm.
Now, in this final section, we will determine the other practical elements of IPM beyond even my expansive view of cost and schedule integration.
Technical Performance Management
Given this paper that resulted from a programmatic effort in Navy regarding Technical Performance Management (TPM), it is probably not surprising that I will start here. My core paper in the link above represents what I viewed as an initial effort at integration of TPM to determine impacts of that performance within program cost performance (EVM) projections. But this approach was based on the following foundations:
a. That the solution needed to tie technical achievement to EVM so that it represented greater fidelity to performance than what I viewed as indirect and imprecise methods; such as WBS elements that contained partial or tangential relationships to technical performance measures, and more subjective and arbitrary methods, such as percent complete.
b. That the approach needed to be tied to established systems engineering methods of technical risk management.
c. That the solution should be simple to implement and be statistically valid in its results, tested by retrospective analyses that performed forensic what-if analysis against the ultimate results.
One need only to look at the extensive bibliography that accompanied my paper to understand that there were clear foundations for TPM, but it remained–and in some quarters remains–a controversial concept that provoked resistance, though programs clearly note achievement of technical requirements. For example, the foundations of technical risk management and tracking that the paper cited were in use at what was Martin Marietta for many years. Thus, why the resistance to change?
First, I think, is that the domain of project performance has rested too long in the hands of the EVM community with its historical foundations in cost and financial management, with a risk averse approach to new innovations. Second, given this history, the natural differences between program management, systems engineering, and earned value SMEs created a situation where there just wasn’t the foundation necessary for any one group to take ownership of this development in systems and business intelligence improvement. Even in industry, such cross-domain initiatives tend to initially garner both skepticism, if not outright cynicism, and resistance by personnel unsure of how the new measures will affect assessment of their work.
But keep in mind that, dating myself a bit, this is the same type of reaction that organizations experienced during the first wave of digitization of work. The reaction to each initiative that I witnessed, from the introduction of desktop computers connected to a central server, to the introduction of the first PCs, to the digitization of work products were met with the common refrain at the time that it was too experimental, or too transient, or too unstable, or too unproven, until it wasn’t any of those things.
I also overstate this resistance a bit. Over the last 20 years organizations within the military services adopted this method–or a variation–of TPM integration, as have some commercial companies. Furthermore, thinking and contributions on TPM have advanced in the intervening years.
The elements of technical performance management can be found in the language of the scope being planned. The brilliant paper authored by Glen B. Alleman, Thomas J. Coonce, and Rick A. Price entitled “Building a Credible Performance Measurement Baseline”, establishes the basis for tying project and program performance to technical achievement. These elements are measures of effectiveness (MoEs), measures of performance (MoPs), technical performance measures (TPMs), and key performance parameters and indicators (KPPs and KPIs). Taken together these define the framing assumptions for the project or program.
When properly constructing the systems, procedures, and artifacts from the decomposition of planning documents and performance language, the proper assignment of these elements to the WBS and specific work packages establishes a strong foundation for tying project and program success to both overall technical performance and the framing assumptions implicit in the effort.
What this means is that there also may be a technical performance baseline, which acts in parallel to the cost-focused performance management baseline. This technical performance baseline is the same as the work that is planned at the work package level for planned work. The assessment of progress is further decomposed to look at the timeframe at that point of progress within the context of the integrated master schedule (the IMS). We ask ourselves as a function of risk: what is the chance of achieving the next threshold in our technical performance plan?
As with all elements of work, our MoEs, MoPs, TPMs, KPPs, and KPIs do not reside at the same level of overall performance management and tracking within the WBS hierarchy. Some can be tracked to the lowest level, usually at work package, some will have contributions from lower levels and be summarized at the control account level, and others are at the total project or program level, with contributors from specific lower levels of the WBS structure.
A common example of what is claimed is a difficult technical performance measure is the factor of weight in aircraft design and production. Weight is an essential factor and must be in alignment with the mission of the aircraft. For example, if an aircraft is being built for the Navy, chances are high that the expectation is for it to be able to take off and land on a moving carrier deck. Take off requires coming up to airspeed very quickly. Landings are especially hard, since they are essentially controlled crashes augmented by an arresting gear. Airframes, avionics, and engines must operate in a salt water environment that involves a metal ship. The electro-magnetic effects alone, if they are not mitigated in the design and systems on both aircraft and ship, will significantly degrade the ability of the aircraft to operate as intended. Controlling weight in this case is essential, especially when one considers the need for fuel, ordnance, and avoiding being detected and shot down.
In current practice, the process of tracking weight over the life of aircraft design and development is tightly controlled. It is a function of tradeoff analysis and decision-making with contributors from many sub-elements of the WBS hierarchy. Thus, the use of the factor of weight as an argument to defeat the need to tightly integrate technical measures to the performance measurement baseline is a canard. On the contrary, it is an argument for tighter and broader integration of IPM data and, in particular, ties our systems to–and thus making the projections and the basis of our decision-making a function of– risk management, which is the next topic.
Risk Management Elements and Integration
There is a good deal of literature on risk, so I will confine this section to how risk in terms of integrated project and program management.
For many subdomains within the project and program management, when one mentions the term “risk management” the view often encountered is that the topic at hand is applying Monte Carlo analysis using non-random random numbers to the integrated master schedule (IMS) to determine the probabilities of a range of task durations and completions. This is known as a Schedule Risk Analysis or SRA.
Most of the correlations today are based on the landmark paper by Philip M. Lurie and Matthew S. Goldberg with the sexy title, “An approximate method for sampling correlated random variables from partially specified distributions”. With Monte Carlo informed by Lurie-Goldberg (for short) we then can make inferences as to alternative critical paths and near-critical paths for time-phasing our work. Also, the contribution of each task in terms of its criticality and contribution to the critical path can be measured. Sensitivity analysis elements identifies the most critical risk elements.
If the integrated master schedule is truly integrated to resource and cost, Lurie-Goldberg allows us to defeat the single-point estimate heavy projections of EVM to calculate a range of cost outcomes by probability distribution. This same type of analysis can be done against the time-phased PMB.
But that is just one area of risk management, which is known as quantitative risk. Another area of risk which should be familiar to project and program managers is qualitative risk. The project and programmatic risk analysis of qualitative risk involves the following steps:
1. Risk identification
2. Risk evaluation
3. Risk handling, and
4. Continual risk management
This is a closed loop system, which garners a risk register, risk ranking, a risk matrix, risk handling and mitigation plans, and a risk handling waterfall chart. These artifacts of risk analysis will also require the monitoring of risk triggers, and cross-referencing to risk ownership.
Once again, though cost impacts are also calculated, with their probability of manifesting, the strongest tie of risk management begins with the integrated master schedule. Thus, conditional and probabilistic branching will provide the project and program team with a step-by-step what-if? analysis that provides alternative schedules that will also provide ranges of cost impact.
Mainstreaming Risk Management and TPM into IPM
In reality, project and program management is simply monitoring and forecasting without technical performance and risk management. Yet, these sub-domains are oftentimes confined to a few specialists or viewed as a dichotomous and independent processes under the general duties of the team.
The economic urgency and essentiality of integrated project and program management is the realization that technical achievement of the product, and the assessment and handling of risks along the course of that achievement, are at the core of project and program management.