SLIM-Estimate

SLIM-Estimate

How does uncertainty expressed in SLIM-Estimate relate to Control Bounds in SLIM-Control? Part II

Several months ago, I presented SLIM-Estimate’s use of uncertainty ranges for size and productivity to quantify project risk.  Estimating these two parameters using low, most likely, and high values predicts the most probable effort and time required to complete the project.  This post shows you how to use SLIM-Estimate’s probability curves to select the estimate solution and associated work plan that includes contingency amounts appropriate to your risk.

Begin with an unconstrained solution

The default solution method used for new estimates, whether you are using the Detailed Method or another solution option, is what we call an unconstrained solution.  Just as it sounds, no limits have been placed on the effort, schedule, or staffing SLIM-Estimate can predict.  It will calculate the resources required to build your product (size) with the capabilities of your team (PI).  Assuming you have configured SLIM-Estimate to model your life cycle and based your inputs on historical data, you have produced a reasonable, defensible estimate.  

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SLIM-Control SLIM-Estimate

Ditch the Madness: SLIM Your Brackets

Monday morning I received an email that read:

Hi All,
You can set your clocks to it: the birds flying north for spring, daylight savings time, and this email being sent on the Sunday before the tournament begins.  That's right, March Madness is upon us my friends, and we’ve officially made it through winter. 

The message continued with details about how to participate, but as you can see, it’s time for QSM’s annual March Madness tournament.  So how do I justify spending company time filling out brackets?  By blogging about how this is actually related to project management.  As I went through the exercise of predicting the course of this tournament, I realized that many of the thoughts I had also go through the minds of project managers.

Before I reveal my picks I want to give some background information.  I’m new to this whole March Madness tournament thing.  I’m not familiar with the teams.  I don’t know the players’ strengths and weaknesses.  I didn’t watch their games earlier in the season, so I don’t know their stats.  All I know is that my significant other went to Ohio State so I want them to win.

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SLIM-Estimate Project Management

Achieving Goals Begins with Successful Measurement

“You can’t know where you’re going until you know where you’ve been.”

At this point, we’re about one month into 2013 and many of us have abandoned our New Year’s resolutions.  Personally, I prefer to set my yearly goals about a month in because it gives me some time to reflect on what I really want to improve without being distracted by everyone’s bandwagon resolutions like getting in shape or eating less junk food.

The other reason I prefer to wait a month before resolving to do anything is because it gives me time to collect some baseline data.  In his Wall Street Journal article, Bill Gates writes, that “you can achieve incredible progress if you set a clear goal and find a measure that will drive progress toward that goal.”

To use the common example of getting in shape, I’m going to explain:

  1. How to set a goal, and
  2. How to measure it so that you can effectively achieve your goal.

First you need to set a baseline measure of what your abilities are.  How fast and far can you run?  How much weight can you lift?  How much do you weigh?  Knowing the answers to these questions can help you determine what needs improvement.  

Next you need to identify your end goal and find a way to quantify progress towards that goal.  What does “get in shape” actually mean?  Do I want to be able to run faster?  Farther?  Do I want to be able to lift more weight?  Do I want to weigh less?  All of these goals can be quantified (e.g. I want to be able to run a mile 30 seconds faster than I currently do, I want to run a 10 miler, I want to be able to bench press 100 pounds, I want to lose 20 pounds).

Why Are Conversion Projects Less Productive than Development?

While doing research on projects counted in function points, the sample size was large enough (over 2000 projects) to allow me to compare the productivity of different project types.  The QSM database uses these project categories:

  • New Development (> 75% new functionality)
  • Major Enhancement (25% - 75% new functionality)
  • Minor Enhancement (5% - 25% new functionality)
  • Conversion (< 5% new functionality)
  • Maintenance

I calculated the normalized PI’s for projects in each development classification compared to the QSM Business trend lines.  The advantage of this is that it takes into consideration the impact of size and shows how the productivity of each project “application type” differs from the QSM Business IT average.  The datasets included medium and high confidence IT projects completed since 2000.  When I obtained the results, I went back over my selection process and calculations to make sure I hadn’t made a mistake.  The numbers were that surprising.  But, no, I hadn’t fat fingered anything (neither physically nor mentally).  Average productivity for conversion projects  was more than a standard deviation below the QSM Business IT average.

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SLIM-Estimate Function Points Database

Agile Series Part 2: Stakeholder Satisfaction

When learning something new, people often try to relate the new information back to something they already know in order to help make sense of the new concept or idea.  As a psychology major now working in the software world, I’ve found myself relating a lot of what I’m learning back to the psychological theories and concepts I learned in college.  Therefore, it is no surprise that upon reading The Twelve Principles of Agile Software, I’ve discovered that many of their principles map to organizational psych concepts.

Agile development theory approaches software development holistically.  I believe this is one of the reasons Agile projects have become so successful.  Rather than merely focusing on skill development, Agile methods foster leadership skills and teamwork among members of the development team itself, as well as between the development team, the project owner, and the stakeholders.  One avenue for this is to unify the development team and project owner with the common goal of achieving stakeholder satisfaction.

The first principle states, “Our highest priority is to satisfy the customer through early and continuous delivery of valuable software.”  The question I had upon reading this was what do the authors mean by the term satisfaction?  When thinking about satisfaction, most people think of outcome satisfaction, or the ultimate outcome of something, in this case the functionality of the delivered software project.  Process satisfaction on the other hand, refers to the level of satisfaction associated with the method of developing the software, or how much the stakeholders enjoy the software development process.

Data is the New Soil

David McCandless gave a TED talk  in July 2010 that focused on pairing data and design to help visualize patterns.  In his talk, McCandless takes subsets of data (Facebook status updates, spending, global media panic, etc.) and creates diagrams which expose interesting patterns and trends that you wouldn't think would exist.  Although the focus of McCandless' talk was about how to effectively use design to present complex information in a simple way, I was struck by his own claim that data is not the new oil, but rather that data is the new soil.  For QSM, this is certainly true!

QSM maintains a database of over 10,000 projects with which we are able to grow a jungle of ideas, from trend lines to queries about which programming languages result in the highest PIs.  With  the amount of soil that we have, we are able to provide insight into the world of software, just with the data that is graciously provided by our clients.  By collecting your own historical data in SLIM-DataManager, you can create your own trend lines in SLIM-Metrics to use in SLIM-Estimate and SLIM-Control, analyze your own data in SLIM-Metrics, tune your defect category percentages and calculate your own PI based on experience in SLIM-Estimate, and much, much more. 

How do the uncertainty ranges in SLIM-Estimate relate to Control Bounds in SLIM-Control?

I am often asked this question during SLIM Training classes.  I remember wondering about that myself.  It is a logical question since SLIM-Estimate workbooks are often imported into SLIM-Control to create the baseline project plan.  The answer is ‐‐ they are not directly related, because uncertainty ranges, probability curves, and control bounds are designed to perform different tasks.  This post is the first in a series looking at risk associated with an estimate, risk of your project plan, and handling deviations from the plan.

What are we talking about?

The first thing we need to do is define some very important terms that are often misused (I am the first to admit I have been guilty!).  I went to good old Dictionary.com and looked up the following:

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Risk Management SLIM-Control SLIM-Estimate

Part III: The Caveats

In Part 1 of How Much Estimation? we noted that there is an optimal amount of time and effort that should be spent in producing an estimate based on the target cost of a project and business practice being supported.

In Part 2: Estimate the Estimate, we saw that the formula to calculate this optimal time (as measured at NASA)  calculates the Cost of Estimate as the Target_Cost raised to the power 0.35 (approximately the cube root of the Target Cost).  The factor that defines the business practice (either by early lifecycle phase or perhaps by the “expected precision” of the estimate) is a linear factor ranging from a value of 24 to a value of 115.

Those Caveats!

I mentioned that there were caveats with the calculation.  Here they are:

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Estimation SLIM-Estimate

Tuning Effort for Best in Class Analysis and Design

After reading Best Projects/Worst Projects in the QSM IT Almanac, a SLIM-Estimate® user noted that the Best in Class Projects expended around 28% of their total project effort in analysis and design (SLIM Phase II) compared to 10% for the Worst in Class Projects. She wanted to know how she could tune her SLIM-Estimate templates to build in the typical best in class standard for Analysis and Design.

In SLIM-Estimate, effort and duration for phases I and II are calculated as a percentage of Phase III time and effort. To create a template for estimating phases II and III that will automatically allocate 28% of total project effort to analysis and design (Phase II), follow these simple steps.

  • From the Estimate menu, select Solution Assumptions.  Make sure the “Include” check boxes for Phases II and III are selected.  Then click on the Phase Tuning tab.
  • Click on the tab for Phase II.  (If you have previously customized the phase names, the default name for Phase II will reflect that).
  • Click on the Manual button under Effort, and enter 28% for the effort percent.

That’s it. Your estimates based on this template will now automatically allocate 28% of total project effort to Analysis and Design (Phase II).

This procedure assumes that your estimates will be for SLIM Phases II and III, which, we have found, is the typical scope for most project estimates. However, if your estimates include Phases I and/or IV, you may have to increase the effort percent a bit to achieve the desired result.

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SLIM-Estimate Tips & Tricks Effort

What If? The Power of the Question

After being away from QSM and the software world for three years, I was blown away by SLIM v8.0's dynamic product integration. I knew it was coming, yet I was still impressed by the simplicity and power of analysis promoted by real-time data and tool links across the SLIM Suite that frees managers to focus on the important program issues.

SLIM-MasterPlan is the center of the SLIM Suite product integration.  It improves upon previously existing program management features of aggregating multiple SLIM-Estimate projects and ancillary tasks with two new capabilities: 

  • Linking SLIM-Control workbooks to provide real-time project tracking and control at the program level 
  • Performing What If analysis at this higher management view to consider a wider range of potential outcomes.

The What If analysis feature is what I want to highlight.

A good personal development coach knows the "power of the question."  Questions lead to discovery, innovation, and action that brings about positive change.  Better questions lead to better answers.  SLIM's power and distinction has always been fast and easy evaluation of the impact of change, and exploring the realm of possible outcomes.  That's what we are doing when we ask ourselves "What If…?" (or our boss asks us - and we better know the answer!).  SLIM's solution logs make it easy to compare estimates, plans, and forecasts to alternative solutions, QSM trends, and your historical project database.