Decision Excellence Agenda Video

This video sets out the Decision Excellence agenda.

http://youtu.be/40DDZc1nejA

Spreadsheet Furore

Every so often, we get a news tempest about an error in a spreadsheet. What seems odd to me is that no one points out that there is a fundamental error in all spreadsheets, a gaping hole that is far more serious for Decision Excellence than the errors people sometimes make.

Spreadsheets don't tell you what you need to know.  

And even if they are correct, they are lying.

All right, I accept that in some circumstances this may not be the case. If you are talking about things like your bank balance, where there is complete information about all the quantities involved, then they can be honest and useful.

The trouble is, they are used to take decisions, and this is where they are letting us down, badly. 

Every decision is a bet, and what is the first thing you need to know before you place a bet? It's the odds, the probabilities, or the term I prefer, the predictability.  

You know very well that it would be a total miracle if the actual number came out to be the same as that in the forecast. So why doesn't the spreadsheet give you information on predictability - the chance that each different possible outcome will come to pass?  For example, the chance that the costs will be greater than the benefits.

It really hurts my head that it is taking SO LONG for businesses to get the capability to manage predictability.  The mathematical methods have been around since the 1950s, and scientists and engineers use them all the time.  

Why is this?  I can think of several reasons. 

First, we don’t tell our children the truth.  We teach them that 2 + 2 is always 4.  But 2 + 2 = 4 is a special case; it only holds when the symbols represent definite quantities.  When they represent indefinite quantities, when there are ranges of possible values for each quantity, 4 is the wrong answer!

Suppose the first “2” in your business case represents infrastructure costs, and that quantity is in the range 1.9 to 2.4 and the second “2” represents application costs, and it has a range 1 to 6.

Then the answer 4 is wrong both numerically and conceptually.  Numerically, 4 is not the most likely sum, and conceptually, it is the range of the sum we need, not just one value from that range.

The second answer is we let people who don’t know this basic truth design our IT systems.  As a result, our databases and spreadsheets all have little boxes in them, and those boxes can only handle definite quantities.

Then to top it all off, we don’t educate our accountants about this. We set them up with bad mathematics, and bad tools, and then we put them in charge!

So we’re stuffed – there’s no way, with the data we have and the tools we have, to get the answers we need! 

Actually, there are tools out there that can do the job, they are just too hard to use. The good news is this can easily be fixed, using Applied Information Economics. Let me explain how.

Decision Excellence: What Does it Take?

Performance is directly attributable to the quality of decisions taken by the people involved. This is true in sports, war, government, economics, personal life - I can't think of a domain where it does not apply. 

So one would expect to see businesses  institutions, agencies, governments and individuals striving systematically for decision excellence. But this seems to be true in only in a minority of cases. 

This presents a paradox and a wealth of opportunities. The paradox is that the problem has been with us for centuries, so why wasn't it nailed long ago? The opportunities arise because when one is starting from a low baseline, substantial improvements can be achieved relatively easily. 

What does it take to achieve Decision Excellence? That is the question this blog addresses.

I'm not going to address the character aspects: the commitment, passion, focus, and steadfastness of purpose; let's take these as given. My concern is HOW, given the heart and the head are suitably configured, one achieves Decision Excellence. What are the components, and how do they fit together? 

I see four interacting components. Any one of these on its own can help move you forward, but when all four are brought into play, their powers multiply. Conversely, leaving any one of them out is like standing on a chair with a missing leg.

The good news is that it is now feasible to bring all four into play in a rapid, balanced and cost-effective way, to achieve outstanding results.

The four parts are the red ovals in the figure below.  They constitute business goals: solving the right problem, understanding the data, working with not against the physics, and managing predictability.

The discipline that delivers each is shown in blue.  Let's go through them one by one.

1. Solve the Right Problem

This is about ensuring we have the most appropriate conceptual framework for thinking about the decision, so we can be sure we have all of the pieces of the puzzle on the table, and that we understand how they fit together.  The way to achieve this is with Systems Thinking, a graphical discipline for building shared understanding and constructing coherent narratives.

2.    Understand the Data

We need to make appropriate use of the available data so we can understand what is happening and how things are changing. This is where Data Science is so powerful. It may even provide clues as to why the changes we see are occurring.  It needs to be recognized, however, that data can only tell us about the past, and what we are trying to manage is the future. We need to understand the past, but that's not all we need.

3.    Work With, Not Against, the Physics

If a business tries to build revenue by increasing its sales force, but fails to invest appropriately in growing delivery capacity as well, that would be working against the physics of the situation and would hinder performance. There is a well-developed quantitative discipline for this, called Strategy Dynamics. Applying it quickly yields important and tangible insights about how to improve future performance.

4.    Manage Predictability

Predictability is the probability of different outcomes, given all the known risks and uncertainties. The great majority of decisions are taken with only superficial estimates of predictability: risks and uncertainties may be captured in a "risk register", but they are almost never incorporated into financial models in a disciplined way. Applied Information Economics is the appropriate discipline here. 

  

I will expand on each of these in my next posts, but to repeat the good news:  it is now feasible to bring  all of these powerful disciplines into play in a rapid, balanced and cost-effective way, to achieve outstanding results.

How does your corporation/department/institution rate for Decision Excellence? 

Take this 5-minute survey to kick-start your thinking.

For more information, contact:   Dr George A Simpson at  gsimpso4@gmail.com