Measurement is a reduction of the uncertainty

In my work I hear quite frequently a lot of smart words. Very often those words are used as a justification to implement one or another project. To keep it short – people spend millions and go through painful change projects because they chase “improved transparency, compliance, control, visibility; increased speed of transactions and operations; reduction in resource intensity; simplified and streamlined processes”. Those are all good reasons. The bad part is – businesses rarely evaluate the benefits in the same units of measure as the price for project implementation. In other words – they simply think it cannot be measured. It is INTANGIBLE.

In the pursuit of attempt to find the answers, I read a book during my recent holidays: “How to measure anything. Finding the value of “intangibles” in business” by Douglas W. Hubbard. Not the best choice for holiday read: according to Lexile framework for reading, it is evaluated at 1240. Almost like reading Stephen Hawking’s “A Brief History of Time”, evaluated at 1290. However, some of the things I found there are brilliant with their simplicity. I would like to share my favourite quotes below.

  • Anything anyone really needs to know is measurable. Including employee morale, reputation, transparency, management effectiveness, value of information, risk of bankruptcy, control and other similar things.
  • Information has a price and a value. The best part is that the initial smallest effort to get the information brings the biggest return on investment (Pareto rules here, too). At the same time, not everything matters. Measure only what is worth measuring.
  • Measurement is a reduction of uncertainty. It is not by any means elimination of uncertainty. To make an informed business decision, you do not need to measure the full population. A sample (representative sample) is enough. Knowing, that it will be impossible to measure EVERYTHING, should not stop you from measuring SOMETHING. Make an attempt.
  • There are a lot of methods to help you measure “intangibles”: focusing of what you know as opposed to what you do not know; decomposing the challenges you are facing; experiments; trials; observations; “catch and re-catch”; measuring traces; historical researches – Google or your colleagues might already “know” the thing you are looking for.
  • Object of measurement is a very important starting point in the process. If you think “improved control” cannot be measured, think of consequences it might bring and measure them.
  • Rule of Five. It sometimes might be as simple as that. Only taking 5 measurements can give you the answer you are looking for (with a confidence of 93.75%). Median of those 5 numbers is the number you are after (Commuting time to work, time on conference calls, etc.). All the difficult details – in the book.
  • Expert judgement (estimation) is also a skill (a tool) which can be improved and calibrated (see here).
  • Categorization and rating (High / Medium / Low) can be very misleading risk assessment methods. Average is not always a good measurement. Compare an average PO value of £516 to a mean PO value of £209. When you are calculating average PO administration costs (£50) per PO in %, the difference is big: 9,7% vs 24%. And now, for the fun of it, imagine you have in total 100k of orders a year… Your priorities in process optimization initiatives for the next year would change, I assume, seeing numbers in different perspectives?
  • “…people do not know how to generate electricity – but they still use it…” There are tools available on the internet and tips to create Monte Carlo simulations on Youtube – almost no excuse not to carry out an assessment when it is really needed.
  • Errors do happen. Intentional, unintentional, systematic, random – you need to keep that in mind when you are trying to estimate anything. By understanding sources and types of errors, you can minimize or eliminate them.

In my experience, I have faced some situations, which looked intangible. Some of the examples where I managed to measure and take action:

  • Economical cleaning efficiency in food retail restaurants and food factories;
  • Organisational structures’ economical efficiencies comparison;
  • P2P systems expected financial benefits versus costs;
  • Behaviour change projects expected efficiency versus costs of change program.

Did you manage to measure something that was considered to be “intangible”? Please share your experience in comments! I would be grateful for examples and I am pretty sure many of us would learn quite a bit!

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Measurement is a reduction of the uncertainty

If I had to put my money on it…

One sentence. That is all you need to reset your brain from simple biases (a.k.a. mistakes in other words). But let’s start from the beginning.

To sum up, logic is not that straightforward

It all started during my holidays. I thought I would do some reading. Which I did. But, besides giving me some tools for my work, the book also challenged my understanding about humans being logical creatures. The book (“How to measure anything” by Douglas W. Hubbard) also talks about perceptions and games that human brain plays. It talks about classical statistics and Bayesian statistics (I am preparing a book overview for my next post. This post is about my experiment).

One of the phenomenons that the book describes is how various biases affect people’s decisions. How perceptions win over logic (say what???). How people choose to believe few pieces of new information and disregard all of the data and facts that they have at hand historically. Having read that, I felt almost insulted for all of us. Oh my saint naivety!

Off to experimenting!

So I decided to test the methodologies and experiments, described in the book. I took exactly the same question, which was used in the book and started asking people around me: “there are 100 specialists in the room. 95 of them are criminal lawyers and 5 – paediatricians. One person was selected randomly. It turned out to be Jane. Jane likes science and she loves kids. What is Jane’s occupation?”.

I started with my partner. First big surprise! On the other hand… knowing how he bought mascara for me… I decided I needed to increase the sample. I tested it with one of my CIPS class students and I was also surprised, again. The final step was to broaden the audience and get the feedback from more people – which I did with a LinkedIn post. I have received many different replies:

  • Statistically most likely. Lawyer. There, I said it – most likely, Jane is a lawyer.
  • Statistically less likely. Paediatrician. This is the grey area. It is not entirely incorrect answer. Explanation will follow later in the text.
  • Different: politically correct, challenging, sensitive, thoughtful, show-off. Knowing, that everyone is first of all a human with a personality, before becoming a professional – you would not expect anything less, right?

Overall the conclusion is one – people are not statistical machines and they are always prone to biases. The book was right. I was wrong to think that people, as a rule, are logical.

The theory

The reason why I avoided to give “the right” answer is complicated. Even statistics is not that straightforward. There are different approaches to it. The book analyses two different approaches – classical and Bayesian.

Classical statistics makes two assumptions:

  1. The data you are analysing has normal distribution.
  2. You know nothing else about the phenomenon you are analysing apart the data you are given.

Needless to say, both of these assumptions many times are wrong. Bayesian statistics, on the other hand, says that whenever you are making a [business] decision, you should take into account (or not ignore) other available information.

In the example given above, you have two portions of information: 95 criminal lawyers and 5 paediatricians; and some new information – Jane’s personal characteristics. Which piece of information do you choose to believe? Which part is more facts based and which is more biased (“standards”, sales and marketing statements, clichés)? That is up to the specialist to decide.

The Application

If you think this is not relevant to you, you are wrong. It is not just a story from a book:

  • Remember every time you hear a sales pitch of yet another P2P system, which “will solve all of your problems”.
  • Remember all the times, when you get a feedback, based on wrong biases and assumptions: no matter if it is recruitment process, annual performance feedback meeting or any other type of feedback.
  • Remember tender evaluation process. I have seen too many tenders, where all of the historical information about supplier performance is put aside, purely because during the tender the new sales team made a great sales pitch. A supplier was always late and delivered poor quality service? And you choose the same supplier again because the sales team promised that everything will change? It is up to you to choose what you believe.

People make decisions based on biases and perceptions more often that they think they do. Scary?

The Fix

There is a fix to it! And it works! I also tested it on myself and my test groups. Almost ALL people who initially chose paediatrician as an option changed their decision when I asked this question: “If you had £1000 and had to put it on your option – what would you do?” (That is also a suggestion from the book). If they had to put their own money on one of the options, they would choose lawyer.

Without going into details, I will sum up: if you are asked a question and you want to give a more confident reply, start it by saying “if I had to put my money on it, I would…”. It is proven, that this helps to re-calibrate your brain. You might still choose the same option, but by saying that, you switch on a different part of brain – that means your reply will be considered from different perspectives.

My reply to the tender evaluation could be: “If I had to bet my money, I would say that the supplier will continue being late, despite what they claimed during the tender. However, even knowing this, I would recommend awarding the contract to them. It is a risk that we already know about and we need to work on it together with the supplier. Instead of being undefined threat, it becomes an action plan and, potentially, a strength”.

 

Hope this is helpful. I thoroughly enjoyed receiving the answers to my question on LinkedIn. Thanks to everyone who contributed! Thank you for reading!

 

If I had to put my money on it…