Written by Bill Adams
Amid this current Data Revolution, tech solutions to help you manage your massive amounts of project portfolio data everywhere. Some even go so far as to deliver graphs and visuals that attempt to aid your understanding, but that data is provided without context or meaning. You would need a PhD in Statistics to extract understandable and actionable information from their data.
So how do you know what your PPM is really trying to tell you? These days, you almost need a Rosetta Stone that can translate your PPM information into plain, understandable, actionable English!
Well, we noticed a gap and came up with a solution.
The main objective of our algorithms and analytics is to provide you with quick to understand, actionable insights of your portfolio options. To achieve this, we needed to create a language that allows you to:
1. Express and understand where you are,
2. Navigate your options, and
3. Communicate those options!
Before we get into our discussion, we need a standard portfolio example to use.
Our Example Model. For the sake of our discussion, let’s assume your portfolio has:
1. KPI’s of Revenue and Customer Satisfaction for your projects
2. Cost estimates
3. Risk estimates
The Rosetta Stone For Your PPM
For each column of measurements on your projects, wouldn’t it be nice to have an A-F grade, for how well your plan does on that column? This is where our Grading Algorithm comes in, the Rosetta Stone for your PPM problem. For instance, say your current plan of projects has the report card:
Then we immediately know several things about your plan:
You are doing essentially as well as possible on Revenue.
You are doing horribly on Customer Satisfaction. You are probably hyper-focused on Revenue at the expense of Customer Satisfaction.
You are over spending (D on Cost) in order to get that A on Revenue.
Your Risk profile is pretty good (B on Risk).
What Grading Gives You
Consider these examples of how grading helps you understand your project portfolio options:
1. Grades are immediately understandable: A grade of an A on Revenue means you are essentially doing as well as possible. A grade of an F on Revenue means you are doing really poorly. Similarly a grade of A on Costs means you are doing really well on your spending, and an F on Costs means you need to do a lot better. It provides context for your numbers, in a way that everyone can immediately understand.
2. Making Revenue Comprehensible: In our example, we have a Revenue KPI for your projects. You can certainly total up the Revenue for the projects in your plan, to get an idea of how well your plan performs on the Revenue metric. If you have a total Revenue of $35 million, is that good or bad? There is no context for the number. However, if you have a Revenue grade of B for that $35 million, you know it is better than your target, but there is room for improvement! All from a single letter!
3. Making Customer Satisfaction Comprehensible: In our example, we have a KPI of Customer Satisfaction. You decide that total Customer Satisfaction should be measured by summing the Customer Satisfaction scores of the projects (each score is a number between 0 and 1, where 0 is horrible and 1 is perfect). If the customer satisfaction score is 52, is that good, or is it bad? Whereas a grade of D on Customer Satisfaction tells you immediately that you are off target, but not as bad as you could be!
4. Overall KPI Performance: In our example you have two KPI’s you want to do well on, Revenue and Customer Satisfaction. It would be nice to know how well a plan does overall on both KPI’s. Yet the columns and sums are on different scales (money versus abstract customer satisfaction). Using grading, in our examples above, Revenue was a B, and Customer Satisfaction was a D. Clearly that averages out to a C overall score on the KPI’s. Grading puts Revenue and Customer Satisfaction on the same scale, allowing you to combine them!
5. Trade-offs: With grading, everything is on the same A-F scale, which allows you to easily perform and understand trade-offs. For instance, your current plan may give an F on Risk and an A on Revenue (you have the possibility of great Revenue but with loads of Risk). However, an alternate plan may have a C on Risk and a B on Revenue. You are trading an F to a C on Risks (becoming less risky) in exchange for sacrificing some upside possible revenue. Those 4 simple grades gives us a lot of information to work with!
How the Grading Algorithm Works
The steps of our Grading Algorithm are:
1. You have a column of measurements on your projects
2. We total up your plan on that column by either:
a. Summing up the scores of the projects
b. Averaging the scores of the projects in the plan
c. Other totaling methods
3. We grade that total using either:
a. A target you have set. Hitting the target is a C, doing better brings you towards an A, and doing worse brings you towards an F.
b. Without a target we explore the universe of possible plans, and compare the score of your plan on that column to everything else in the universe, to get a percentile score. We then convert that percentile into a letter grade.
You need a language to speak about your options to understand them, you also need that language to navigate through them, and finally you need that language to communicate them to decision makers. Meanwhile those decision makers need that language to communicate their plan and their reasoning in choosing that plan.
Our grading methodology solves these problems, allowing you to:
1. Understand: With grading, you immediately understand what an A on Revenue means or an F on Costs means, etc.
2. Navigate options: If you have an F on Revenue, you immediately know which direction you need to navigate. Grades tell you the directions available for you to move. They also make navigating trade-offs easily understandable. For instance you can sacrifice from an A to a B on Revenue in exchange for less Risk (going from an F on Risk to a C).
3. Communicate: Grades are immediately comprehensible, making them easy to communicate to others, so that they can understand what is at stake.
Want to learn more? See how advanced algorithms discover and highlight your best possible portfolio level options.
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