Benchmarking Big Data Business Forecasting Data

The Semantic Approach to Building Accurate Project Plans

An idea.  Alone and unshared, while of great potential, worthless in the wild.  In the consumer space, ideas are tweeted, trending, memes, most popular and can even go viral.  The 140 characters of Twitter and the brief updates on Facebook, singular or compound ideas, are being used to target marketing.  In the consumer space, ideas have value.  It costs over $54 dollars (Google Adwords) to tap into the buy insurance idea.  So what about in the business enterprise?

For over 60 years with the advent of modern project management, ideas happen once, and then the work begins.  No trending, most popular, nothing like a business segment meme, or even the winning idea going viral.  We keep developing a project plan like it is a one off exercise with no recognition that the past shapes a new project’s prospects for success.  The project – one off things we do very poorly (less than 50% full success rates).  Sounding more and more like the definition of crazy.

Last year, I completed an in-depth study of ideas in the workplace.  I consciously decided not to use the idea word, as it sounds so, well, fluffy.  I use lexeme (a basic unit of meaning), a word borrowed from linguistics.  I also use lexemetry to describe the process, measuring lexemes in a context.  For me, that context is projects.

Here’s what I did.  First, I had already developed an engine that does semantic matching.  While it can look at any string, I focused on task titles for this research.  For each task, the matching engine looks for other task titles that semantically match the new task title.  New matches are added to a matchset cache.  Now, we have a subset of all tasks that match semantically.

500px-Semantic_Net The premise is the tasks that match, those that happen more than once in a project portfolio, form the cogs of what makes the day to day project assembly line operate.  These matchsets are the iterating steps of a formal process. They are multiple copies of project templates.  The matchsets are also things that everyone adds to projects based on the culture of the enterprise.  They are the crowd sourced knowledge of the way to get projects done.  Also, iterating tasks allow us to build models based on the matchsets – cost, roles, durations, efforts, movements, relationships, all the metadata of project work.  In fact, I’ve argued that the bulk of our enterprise big data is meta of work/performance.  Thus, these matchsets are actually the Higgs Bosons of enterprise big data – everything else is created from work.  As such, the matchsets can also provide insights into those tasks that don’t match, the value givers.  With models we have benchmarks.  With models we have ranges.  With models, we can even evaluate worst, bad, abnormal, normal, good and best.

While we could look at any other meta of the matchsets, I wanted to do something with time.  Yes, flexing our analytical muscles.  I wanted to show that these matchsets are not just static ideas/lexemes glued to the projects where they occurred.  They move, they materialize in different parts of a schedule.

However, time comparisons are not a simple endeavor.  Projects have different durations, and June 15th is comparable to what?  We need to normalize time across projects.  We chose percentage as our canonical form for time.  Thus, the beginning of the project becomes the 0 percentile of time, while the 100 percentile becomes the end of the project.  Now, all time is directly comparable, and all of our matchsets live in this normalized time.

We have some cogs of commerce iterating in time, so what can we tell from this?  We can find benchmarks, mine process, and even identify best practices.  But first, our data.  I randomly selected data from a few databases. I also ensured that I did not get all similar businesses or industry types.  That resulted in just shy of one million tasks in over 20,000 projects.  I found:

  1. At least 40% of tasks are iterative.  We have a benchmark.  I’d also like to say that the concept that all projects are one offs is a dead one.  Almost one out of two lexemes in your project is iterative.  Plan on it.  Use it to your advantage.  Understand your iterating ideas via measure.
  2. On average, lexemes can deviate in time by 11.52%.  We have a benchmark for a task buffer.  The critical chain folks are going nuts!  To me, this so fundamental.  We have a statistically significant finding of an empirical number that shows how difficult it is to schedule and perform work.  Any piece of work can move by around 10% of the project timeline!  Conversely, we can use this bedrock datum to better plan.  Agile, your stories now have a time scale.
  3. Look at this composite process I mined out:
Matchset Master Title Start Percentile
Develop Project Charter 4
Project Initiation Activities 5
Develop Preliminary Plan 6
Update Charter 10
Complete Charter 12
Provide Detailed Plan 13
Develop Communications Plan 23
Identify Supply Chain 27
Develop Requirements 30
Execution Phase Start 42
Development Complete 43
Deployment 69
Execution Complete 70
Deploy to Production 86
Training 86

At a very large company, I found the commonalities in the plethora of templates across many business units. Additionally, I found over 80 lexeme matchsets (in proper time sequence and proper time distance) that were being consistently added to these project plan templates – sub project assembly lines.  Lastly, their very traditional waterfall approach resulted in actual project work consistently not starting until almost half way into the project!

I believe that knowing the benchmark iteration number (40%), as well as the benchmark time deviation number (11%), project success will increase for any enterprise.  It is time the enterprise got its meme on, as lexemetry is poised to go viral.

Business Optimization Project Management

Project Managers, Our Next Action Heroes

In the movie 2012, intense solar storms force mankind to abandon Earth.  Project management certainly played a key role in building the arks needed to evacuate mankind.  Here in the real world, we actually do face a serious threat from solar storms, and project management is our best bet to overcome the devastating effects of the next big storm.
A very active region on the sun, AR2192, is currently Earth facing and throwing off x-class solar flares.  So far, none of these have produced a coronal mass ejection (CME).  Maybe tomorrow, but certainly someday, the Solar Influences Data Analysis Center (SIDC) at the Royal Observatory of Belgium will issue an alert that will call on us to be project management optimum.

Forty-two hours after the alert, the time it would take for the charged particles to reach Earth, our technological society will regress to 1859, the last time an event of this magnitude transpired. In 1859, a series of CME’s known as the Carrington Event fried the fledgling telegraph system.  The 1859 Internet.  Auroras were seen as far south as Cuba!

Forty-two hours after the SIDC alert, we will find out how good we are at project management.  We will find that, at best, way over half of everything we do will either fail completely, take much longer than we anticipated, or cost more, taking away resources from other critical priorities.  Based on forensics of past CME’s and the rate of CME’s observed by satellites for the last 30 years, a Carrington-level event has a 12% likelihood of occurring in any ten year period.  With those odds, a Carrington-level event is 30% likely before the end of this century, and virtually assured by 2200.

I’m not crying wolf, we just missed a Carrington-level event by one week on July 23rd, 2012.

Forty-two hours notice.  With all of the wonderful opportunities we as a species have in front of us, along with the great challenges that we face, project management is becoming the common enabler.  Of any on171879main_LimbFlareJan12_lge thing that mankind can do to decrease the greatest amount of risk is to make projects predictable.  I call it project management optimum.  While we will be devastated by a Carrington-level CME event, we can recover faster, saving countless lives, if we are project management optimum.  The only way for SpaceX to get to Mars, within any reasonable expectation of funding, is to be project management optimum.  Of note, a CME direct hit is just the most clear and present danger.  I would think that any engaged person could come up with several grave dangers and wondrous opportunities that project management optimum could address.

We will have seen our demise coming for forty-two long hours.  The US General Services Agency (GSA) recently conducted a challenge for describing what project management would look like in 2039.  What is needed is a bigger challenge, an actionable challenge.  What is needed is an x-Prize like completion to consistently forecast cost, schedule, and risk; the pillars of project management, at the 95th percentile of accuracy or above.  We have the data to do this today, we just do not have the algorithms.  The research is out there, just not system engineered into a solution set.  Google “$100 million investment,” and you will see nations, states and even cities and companies investing funds of this size.  For that amount, GSA could set up the investments and prizes to get us to the 95th percentile.

A 30% chance in the next 86 years and only 42 hours’ notice.  It’s time to make project management optimum a national priority.

Government IT

A Vision for a New Era of Project Management – Bootstrapping a Solar System Civilization

The White House Office of Science and Technology Policy asked for entrepreneurs and visionaries to submit their ideas for bootstrapping a solar system civilization.  OK, here you go.

The Inefficiency Tax – Huge Friction At Any Mass

Regardless of how we attempt our immigration to other worlds, bootstrap or pay today’s estimated full price, an inefficiency tax will be levied.  In a 2012 study, McKinsey & Company found “On average, large IT projects run 45 percent over budget and 7 percent over time, while delivering 56 percent less value than predicted.”  It is very likely that the average inefficiency tax is more like 50 percent, as IT projects are much more mature than most corporate projects.

However, we do not have to pay this tax.  We can overcome this tax.  We can enjoy refunds from an ever increasing efficiency.

The greatest payoff, one that will impact every facet of the civilization of space, is to become project management optimum.  Projects are the delivery mechanism, the new assembly line, for anything of real value.  In fact, Tom Peters has said, “All work of economic value is project work.”  Yet, due to our inefficiency in planning and executing project work, everything we do costs more, takes longer, and delivers less than we planned.  If we have any hope of becoming solar system migratory, we must become project management optimum.  Project management optimum delivers at six sigma: on time, within ±5 percent of cost, and with more scope/stories than originally planned.  Project management optimum will stop the levying of an inefficiency tax.

Many trends are moving us toward project management optimum.  Overall, project management maturity has increased, with the importance of the project now seen in all areas of the corporate world.  Marketing gets that it too is project driven.  The CFO has become a believer.  GSA even conducted a vision for the future on for public sector program management.  However, the most impactful trend is the over hyped, yet powerful reality of big data.  Big data – the variable resolver.

That’s what projects do, they resolve variables.  At their best, projects anticipate variables.  At their optimum, projects identify and help communicate the choices of the variables while recommending a best course of action.  As projects become more complex, variables increase on the exponential slope.  While we humans are great at spoting patterns and trends, project management artifacts do not lend themsleves to easy pattern or trend recognition.  We need to rethink the summation of project artifacts in project management optimum.

Thus, the call for mining lexemes in my winning paper.  Lexeme is defined as a basic lexical unit of a lexicon, consisting of one word or several words, considered as an abstract unit, and applied to a family of words related by form or meaning.  Semantic similarity.

Amazon buying recommendations, Google search, Facebook friend do-you-knows and NSA phone call metadata analysis have demonstrated that graph theory and small world algorithms are very accurate forecasters.  To get to project management optimum, we must build context specific graphs of lexemes at work in projects.  We must build these models pan-project, pan-program, and pan-nation/language.  We must define protocols for sharing lexemes and their metadata.  We must discover new insights into language and the short term evolution of language to identify trending lexemes that are nearing meme-birth.  Memes, when viral, are the project’s best friend, yet many times, its worst enemy.  Best to know which.

I believe like Carl Sagan that, “Exploration is in our nature.  We began as wanderers, and we are wanderers still.  We have lingered long enough on the shores of the cosmic ocean.  We are ready at last to set sail for the stars.”  It’s a long trip, though.  Let’s start our journey with project management optimum.  Of all the technologies that we will have to enhance or invent, becoming project management optimum will be by far the cheapest.  However, it may well have the most impact.