G.R.A.S.P. and Schedule Data Credibility Profile

Cognitive Project Management strongly believes that, when it comes to the quantity and quality of useful information to be taken from that bedrock Project Time Management ritual known as Schedule Updating, which is repeatedly performed throughout the project life cycle, we overlook far more than we recognize.

Properly executed, our Project Time Management processes are capable of yielding a plethora of significant temporal insights — of supreme importance to the Project Team’s approach to upcoming work prosecution — that are simply not at all revealed by the current “monitoring and controlling” processes advocated by Dominant Project Management.

Before we identify the kinds of useful information than can be gotten from a properly understood analysis of contemporaneous temporal data, we need to establish some new terms and concepts.

Introducing the Concept of Schedule Tense

Let us begin by making the observation that all Schedule Elements (activities, relationships, path segments, paths, milestones, Momentum CheckPoints, etc.) are more fully understood in the context of what Cognitive Project Management calls Schedule Tense. All Project Schedules can speak in past, present, or future tense. Cognitive Project Management has expanded this simple truth in order to recognize three Project Performance Periods and three corresponding Schedule Segments.

Defining the Project Performance Periods

The Dominant Project Management model only recognizes two Project Performance Periods: Past Period and Future Period, the two separated by a value called the Data Date, which denotes the end of the current reporting period. Important to this discussion, the Data Date is a theoretical point in time that, in itself, has no duration. Thus, all Schedule Elements that precede the Data Date are, by inference, reflective of the Past Period, whereas all of the other Schedule Elements must be contained within the Future Period. Like I said: Past Tense and Future Tense, but not Present Tense.

By contrast, Cognitive Project Management defines the Past Performance Period and Future Performance Period, not in terms of some dimensionless Data Date but instead, by a clearly defined Current Performance Period. The Current Period covers a span of time that is calculated based on two factors: the Project Length and a predetermined Current Period Percentage variable. (ICS-Protocols recommends using 5% of Project Length, but each Project Team should set its own percentage).

  • The all-important Data Date is to be found somewhere within the Current Performance Period, usually somewhat left of midway. Its placement allows definition of two sub-periods within the Current Performance Period.
    • The Just Done Period spans from the start of the Current Period and ends at the Data Date.
    • The Imminent Period begins with the Data Date and extends to the end of the Current Period.
  • ICS-Protocols recommends a default placement of the Data Date at roughly 20% of the distance between start and end of the Current Period; however, the Project Team should make its own determination based on what is best for achievement of its Project Management objectives.

Putting the pieces together, then, the Past Performance Period spans from Start Project to the start of the Current Performance Period. Likewise, the Future Performance Period spans from the end of the Current Performance Period to Complete Project.

Defining the Schedule Segments

So far we have been talking about Project Performance Periods, which characterize real stages in the real project. But, just as Activities are Schedule Elements that represent counterpart Actions in the real project, so too Schedule Segments correlate with Project Performance Periods. Thus, a Project Schedule can be divided into three sections: Past Segment, Current Segment, and Future Segment.

It should be noted that the proper labels are Schedule Past Period Segment, Schedule Current Period Segment, and Schedule Future Period Segment. But, in the interest of brevity, we truncate the terms to Past Segment, Current Segment, and Future Segment. By either formal name or nickname, these new designations will be central to our understanding of the Schedule Data Credibility Profile, which we will introduce below.

Schedule Tense and Schedule Data Perspectives

Armed with these new terms, we are now able to hold a brief discussion that appreciates the unique contextual perspectives of the different Schedule Segments. The following may seem obvious, but it is good nonetheless to set it down in writing:

  • Past Period data is contextually retrospective. This makes perfect sense. Past Segment data reflects Past Performance Period activities and conditions that took place before the Data Date, and before the Current Performance Period. Whatever we might say, think, or report about past events and circumstances can only be retrospective.
  • Conversely, Future Period data is contextually prospective. Schedule Data from the Future Segment reflects our best estimates and projections of what will happen sometime in the future, after the Data Date, and after the Current Performance Period.
  • As for all Current Period data, this is where the Project Team is at its most introspective. And we can make a further observation, concerning those sub-period timeframes of Just Done Period and Imminent Period. We might characterize the Just Done Period as depictive (i.e., it emphasizes recent achievement with vividness of detail). Quite differently, Imminent Segment Data is principally directive.  Think of the Short-Term Look-Ahead Schedule that provides day-by-day details as to what is to be accomplished, in what order, and by whom.

The reason we want to characterize the contextual nature of the data found in each Schedule Segment is to heighten our awareness of the practical limits of information taken from any given Schedule Segment. If the previous sentence is still a little hazy, the next discussion should clear it up.

Introducing GRASP

According to the Online Dictionary, to grasp means to: “to get hold of mentally; comprehend; to understand, especially with effort.” An interesting discovery that ICS-Research made a few years ago was that, within each Schedule Segment, one can find two different types of schedule data.

  • Past Segment Data: In the Past Segment, schedule data can be divided into Realized Data and Gleaned Data. Since the word, realize, means to “make real, give reality to,” Past Segment Data tells us what actually happened. In business, one might say, “in the last quarter we realized a modest profit.” In the context of Realized Data, we are speaking about information that reflects what actually happened.
  • Contrast Realized Data with Gleaned Data, which results from an interpolation of Realized Data. As an example, when we estimate the amount of time needed by a partially-completed activity to become 100% complete (expressed as a Remaining Duration), we are generating a piece of Realized Data, because the Remaining Duration acknowledges, in the corollary, the work that has been accomplished. Yet, when we perform a Forward Pass on all Remaining Durations, we generate a new set of Early Dates, which constitute Gleaned Data.
  • Current Segment: In the Current Segment we find Apparent Data, the name suggesting that what just took place in the previous week or so is as apparent to us as the work that needs to be performed in the upcoming few weeks. The word, “apparent,” means “readily seen, exposed to light, or open to view.” We can subdivide Apparent Data into its Just Done Segment and Imminent Segment subcategories. Just Done Data is fresh in our minds. Imminent Data is what we are currently making final preparations to execute.
  • Future Segment: Notice that Past Segment data types, Realized and Gleaned, differ by their origins. Realized Data emerges from the work itself, whereas Gleaned Data results from our interpretation and analysis of Realized Data. /the Future Segment also has two very different types of data.
  • Compare this observation to Future Segment data types, which differ in terms of why we generate the information. Strategic Data is formulated from analysis of Realized, Gleaned, and Apparent Data, in order to chart a fresh strategy from piloting the project from the Current Period to Project Completion. Predictive Data has an entirely different intent: to speculate on how the project will turn out, in terms of previously-established goals.

These five types of Schedule Data comprise Cognitive Project Management’s G.R.A.S.P. concept: Gleaned and Realized data, Apparent data, and Strategic and Predictive data.

Introducing the Schedule Data Credibility Profile

Having identified and defined the three Schedule Segments and the five Schedule Data types, it was now possible for Cognitive Project Management to realistically map the variable reliability of the typical Project Schedule. We call this model the Schedule Data Credibility Profile.

F1206-Figure 1

Figure 1 correlates the reliability of Schedule Data with its position along the project timeline. We can make a few observations based on further ICS-Research study into what the Schedule Data Credibility Profile tells us:

  • Schedule Data Integrity Improves Across the Project Length: As a general statement, all types of Schedule Data tend to collectively improve as the project progresses. But now, let’s look at the quality of Schedule Data within specific Schedule Segments and sub-Segments.
  • Realized Data Accuracy Correlates to Data Acquisition Frequency: This is not much of a revelation, since most of us already knew this.  The more frequently we update the schedule, the more reliable the Realized Data being reported. This is because the information is fresher in our minds, having just happened.
  • Gleaned Data Accuracy Gets Better with Time: Now this one might not be as obvious. Gleaned Data, you will recall, is information that is interpolated from Realized Data. But while Realized Data is reporting period specific, Gleaned Data is cumulative of all past reporting periods. So, as more reporting periods drift into the Past Segment, the amount of history, specific to this project, increases.  Gleaned Data for the current reporting period is tempered by trends building across all prior reporting periods.
  • Apparent Data Reliability Correlates with Width of Current Period: But for the comparatively short Just Done sub-Segment data, the overwhelming majority of Apparent Data is found in the Imminent Period. Since the overall Current Segment is proportional to the Project Length, on very large projects it is possible for the Imminent Period to exceed ten weeks. This could be a problem.
  • ICS-Research has determined that there is a direct correlation between a schedule’s level of detail (expressed as the Schedule’s average activity duration) and the service period for that detail. The ratio is 10:1, such that the details remain credible for ten times the average activity duration. For example, if the average duration is ten days (two weeks), then Schedule Data remains reliable for about twenty weeks.
  • The problem with Imminent Period data is that is typifies the most detailed that the Project Schedule might ever get. The Average Activity Duration for a short-term, Look-Ahead Schedule might only be two or three days! Applying the above ratio, the reliability of such a precise schedule edition might be as short as four to six weeks. If the Project Length is quite large (more than two years), it is possible that the Imminent Period might be greater than the four to six weeks.
  • Strategic Data Reliability/Coverage Period Inversely Proportional: What this bullet says is that there is an inversely proportional relationship between the reliability of Strategic Data and the width of the Future Period. This should make perfect sense.  The longer the Future Period, the greater the Uncertainty about threats or opportunities that might wait in the wings.
  • Predictive Data Credibility/Coverage Period Inversely Proportional: Likewise, the same correlation exists with respect to the reliability of Predictive Data.

In Closing

Just what does all of this mean? The answer to this question is the subject of a companion blog at ProjectTimeManagement.com.  I invite you to hop over there and see what it has to say. I hope you have enjoyed this discussion about this brief introduction to GRASP and the Schedule Data Credibility Profile. If you are interested in learning more about either, CPM Mechanics has two chapters dedicated to these all-important topics. To get your copy of the book, click here.

1 Responses to G.R.A.S.P. and Schedule Data Credibility Profile

  1. Zach Reed says:

    Good thoughts on schedule credibility and the “aging” of a schedule. Additionally, I find this a good analysis of the different segments of a schedule and the data therein. Looking forward to learning more.

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