In my previous post, I focused on Program and Project Management in the Public Interest, and the characteristics of its environment, especially from the perspective of the government program and acquisition disciplines. The purpose of this exploration is to lay the groundwork for understanding the future of program management—and the resulting technological and organizational challenges that are required to support that change.
The next part of this exploration is to define the motivations, characteristics, and disciplines of private industry equivalencies. Here there are commonalities, but also significant differences, that relate to the relationship and interplay between public investment, policy and acquisition, and private business interests.
open data
Potato, Potahto, Tomato, Tomahto: Data Normalization vs. Standardization, Why the Difference Matters
In my vocation I run a technology company devoted to program management solutions that is primarily concerned with taking data and converting it into information to establish a knowledge-based environment. Similarly, in my avocation I deal with the meaning of information and how to turn it into insight and knowledge. This latter activity concerns the subject areas of history, sociology, and science.
In my travels just prior to and since the New Year, I have come upon a number of experts and fellow enthusiasts in these respective fields. The overwhelming numbers of these encounters have been productive, educational, and cordial. We respectfully disagree in some cases about the significance of a particular approach, governance when it comes to project and program management policy, but generally there is a great deal of agreement, particularly on basic facts and terminology. But some areas of disagreement–particularly those that come from left field–tend to be the most interesting because they create an opportunity to clarify a larger issue.
In a recent venue I encountered this last example where the issue was the use of the phrase data normalization. The issue at hand was that the use of “data normalization” suggested some statistical methodology in reconciling data into a standard schema. Instead, it was suggested, the term “data standardization” was more appropriate.
(more…)Open: Strategic Planning, Open Data Systems, and the Section 809 Panel
Sundays are usually days reserved for music and the group Rhye was playing in the background when this topic came to mind.
I have been preparing for my presentation in collaboration with my Navy colleague John Collins for the upcoming Integrated Program Management Workshop in Baltimore. This presentation will be a non-proprietary/non-commercial talk about understanding the issue of unlocking data to support national defense systems, but the topic has broader interest.
Thus, in advance of that formal presentation in Baltimore, there are issues and principles that are useful to cover, given that data capture and its processing, delivery, and use is at the heart of all systems in government, and private industry and organizations.
(more…)The Future — Data Focus vs. “Tools” Focus
The title in this case is from the Leonard Cohen song.
Over the last few months I’ve come across this issue quite a bit and it goes to the heart of where software technology is leading us. The basic question that underlies this issue can be boiled down into the issue of whether software should be thought of as a set of “tools” or an overarching solution that can handle data in a way that the organization requires. It is a fundamental question because what we call Big Data–despite all of the hoopla–is really a relative term that changes with hardware, storage, and software scalability. What was Big Data in 1997 is not Big Data in 2016, and will not be Big Data in 2030.
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Life, Project Management, and Everything 