Data Driven? Or Process Driven?

I believe, George, that you and I may be cut from the same cloth.

I agree one can gain much understanding from looking only at N organization's meta data and then properly structuring it into what could be called a discovery data model.

Bill,

Please indulge the theory-basis for my thoughts:

“Knowledge is the accelerant that, when applied to a flame, produces the energy one needs to succeed.”

In the context of business requirements, the platinum standard I’m referring to relates to the knowledge source (i.e., the “accelerant”) that produces the highest energy output to drive your project (as represented through the “flame”) forward to success.

Our options are:

[1] – Knowledge provided through process-based statements: As elicited through documentation, subject matter experts, leadership, and the like—Qualitative knowledge.

[2] – Knowledge provided through behavioral examinations of facts (i.e., data): As elicited through examination of historical data—Quantitative knowledge.

Yes, and to the point of your statement, a project manager operating under good practices should treat these options as “mutually inclusive” (i.e., they happen simultaneously and cannot be separated) and expose all the knowledge to challenged-based review by the stakeholders.

Unfortunately, this good practice often falls victim to project politics surrounding customer correctness; that is, the knowledge (normally qualitative-based) your customer provides is, by definition, the “project fact” that will initiate your project. If the knowledge lacks the energy to drive the project toward objective success, then “so be it,” it’s what they provided, end of story.

Hence, it seems appropriate to call out the perspective that data-driven behavioral-informed knowledge finds more basis in fact through its quantitative qualities than qualitative knowledge exposed through “process-based definitions” provided by humans. Both are needed, but one stands superior in its veracity.

George

Hello Rami Kaibni. I agree with you. Healthcare poses an interesting scenario in terms of data-driven or process-driven. Data gives you facts at the point of care, and process ensures a standard operating manual is followed—a key component in healthcare, where while innovative processes are good, time-tested ones are critical.

In my opinion, both data and process driven are key in healthcare project management.

Hi Keith,

Without [1] business domain, [2] project objective, [3] schema, and [4] technical data interrogation knowledge/skills, you will face some degree of bootstrapping (i.e., the chicken or egg dilemma), and then as you said, there’s that “minor issue :-)“of interpretation.

So, what do you do?
[A] Reject the proposition and move forward with the qualitative knowledge you have.
[B] Solicit the behavior data from the customer and then “challenge out” possible confirmation biases.
[C] Bring in external resources as part of the project to accomplish this task.
[D] Use internal resources to navigate and challenge your way through the menagerie.
[E] Something else.

I would say that it’s not as complicated as it would seem, although I’ve seen an entire team abort a project due to an application-level bootstrapping issue that overwhelmed the team analogous to a social contagion.

That said, If you can consolidate the four knowledge/skills areas above, then you can open the door to the “chicken coop” and start building the metadata-level knowledge that will allow you to break through the questions of “where to start” and “what am I looking for.” Once you have the landscape at your fingertips, you can start building the measures that will allow you to contrast the knowns, and then, from there, you can endeavor into the unknowns.

It’s not an all-or-nothing proposition for completeness or accuracy, as the goal is to challenge the knowns, and that happens whether the contrasting data presented is deemed correct or not, as perspectives will find themselves challenged in the process, and the project will benefit.

George

Keith Novak I agree with you on the dilemma of chick and the egg. In my opinion, its both, data and process driven that are important.