Decisions&Models

Let’s first start with an apology: this article is filled with personal business reminiscences and reading/learning references.

I will start from the end- with a personal joke.

Last Friday, after work, I was doing in a pub my usual “relaxation” exercise- concentrating on pondering each word of few pages within a book on a subject that has nothing to do with my current work, while sipping a beer and being surrounded by a noisy crowd and music.

It is a kind of “mental training” that I practised first I think in late 1980s, when I started travelling on a daily basis between projects across Italy, and then abroad.

After few minutes, a woman asked what I was reading (well, do not disturb me while I am doing my reading exercises :D), and I replied with a smile by showing the title page of the book, and then stating the subject “behaviourial economics”- to which replied with “and you can understand it?”.

Well, as somebody else said… I can resist everything but the temptation- therefore I replied with “that’s what I have been doing over the last 20 years” 😀

The result was the one expected- being able to get back to my book for few minutes more.

But I wasn’t boasting- I was just stating something as obvious as in Moliere “I have been speaking in prose all the life without knowing it”.

Reading “Basic instincts” on behavioral economics reminded me of course of all the usual suspects (my collection of books from Philip Kotler, from the “Marketing” Bible to “Marketing Places” and “High Visibility”), but also two books that I bought in the 1990s just for fun (“All Consumers Are Not Created Equal” and “Marketing senza pubblicita'”), along with some considerations in “Quaderni dal Carcere” that I had to dig in mid-1990s to help a friend complete her thesis in Journalism in Latvia.

Keeping my backward walk through time- the reasons why I read those books was quite simple: in late 1980s I was designing or writing decision making models, using my limited experience in expert systems (PROLOG and PASCAL programming) and theoretical GDSS (i.e. Group Decision Support Systems, thanks to some books published o.b.o. NATO by a Dutch publisher) knowledge.

Also, in the university I had the chance to analyze the decision making patterns of my fellow students in the laboratory on VAX, so that I could prepare few free software tools to solve the typical issues.

The tools that I was used to develop models were distributed in Italy by Andersen (I worked for one of their units), and produced by Comshare, a company originally developed to deliver time-sharing services.

The interesting part on the main tool (a PC-based application, pre-Windows) was that models had three levels: multiple dimensions of analysis (e.g. region, product, market segment- with a hierarchical structure), variables (and formulas linking variables) that could apply in certain levels within dimensions or certain dimensions, and the time element.

But the models that I was building weren’t theoretical models- the knowledge and “reality check” came from the managers of Andersen’s customers.

And the tool had the usual “what if” (what you do everyday in Excel- enter values, and see results), along with a feature that I used often with more advanced models, to predict demand or break-even on specific products and business lines.

This feature, goal seeking (enter a target number, select a bunch of variables across dimensions, and see the value that you should have to obtain your target), allowed to refine models, as sometimes applying the “pure” market model (i.e. reducing marginal costs) produced results that the managers said were impossible- and therefore the model had to be adjusted.

The concept was: while a “what if” model is built on your assumption of the rules required to produce what you did in the past, a goal seeking model tries to change the “inputs” to your model, and can show the fallacies in your assumptions- while revealing the real model used to produce decisions.

This allowed to understand and model real decision making in business contexts: two years in dozens of companies in multiple industries, often one or more models to review or sketch each day, and working in a multinational environment, with occasional “sales and marketing training escapades” to London, where the teams where all multinational.

Now, let’s shift forward in time.

While I had to read and study some accounting while working on a General Ledger project, I recovered some book on international economics from when I was in politics, read some old documents (it was pre-Internet) from my European Federalist times, and tried to reconcile what I observed with readings from books economics (including Adam Smith and re-reading book 1 of Karl Marx Capital- I was tired of people saying to be inspired by this or that… that they had never read, as I discovered when I read :D).

But then I moved from quantitative models, to designing and delivering processes, managing projects, and negotiating the introduction of new processes- what is commonly called nowadays change management of “facilitation”, “coaching”, and so on.

This created a desire to find a framework, a theoretical foundation to what I had observed- hence, two Summers spent at LSE on International Political Economy (including studying “Agents of Change” and plenty of Foreign Affairs and HBR articles), along with another course on Intercultural communication and management- in both cases, to focus on macro issues.

The newly acquired knowledge was part a confirmation, part a discovery, but I also discovered (belatedly- but this is the way of serendipitous need-to-know learning) the “externalities” issue- thanks to a book on a personal MBA experience that discussed in details “A Theory of Justice” (I book that I was to give as a gift to few people), and bibliography during my LSE courses.

The result? I subscribed to the “World Outlook”, “Harvard Business Review”, “Sloan Management Review”, while reading also some annual factbooks- further expanding the study on the feed-back of externalities on business environments.

The interesting part of all this was trying to build and use a framework- and observing how managers really work and decide- and, frankly, I saw often a “tunnel vision”, focused first on the long term viability of their outfit (and effect on their CV should they move), then their team, then the shareholders, then the customers.

Externalities and stakeholders? no, not really part of the picture- until recently, at most “lip service”.

If you want: “us vs them” and “my enemies’ enemies are my temporary opportunistic friends” are the shortest description of the “modus operanda” of real world managers, when working quantitatively.

But, admittedly, in the last decade I worked mainly on the “qualitative” side (project management, negotiations, organizational charts, optimizing/auditing processes, governance), while keeping my quantitative skills alive with support to the most self-conscious and self-obsessed crowd- startups (business and marketing plans) and SMEs/partnerships.

Lining up all this was interesting, as I was constantly exposed to different conceptual frameworks, from long-term continuity and regulatory impacts, to short-term observation of marketing issues.

The more you move to the qualitative aspects, or increase the size of the company, the more conscious managers become of externalities.

It is as if a company were organized around the Maslow’s scale, while pretending to follow the “Seven Habits of Most Effective People” or the “OECD Guidelines For Multinational Companies”

It is anyway appropriate: shielding the experts from the complexities of social interaction increases efficiency.

Some quirky side-effects can be the net result, when detaching the qualitative from the quantitative.

Such as, in 1990, a colleague proudly showing me the record structure for a file were they had concentrated, for an insurance company, all the “negatives” that should be considered in setting a price and their probabilities- death, terminal illness, loss of a limb, and so on.

And that’s why I am always been more than skeptical of purely quantitative management methods that are not restricted to the operational level, but are used to set strategies.

You quantitatively model what you know (tunnel vision), or you build a quantitative model of an unknown based on information that you cannot verify.

You are actually creating your own veil of ignorance- but thinking to have perfect knowledge.

Usually the model is so expensive to build, that reality has to be oversimplified.

I give you a final practical personal business example.

When I started in 1993 by chance (I negotiated to work 3/4 days a week) to work as a consultant on change management, I did not know how to price myself.

I did the mistake that “standard” economics say: I took my salary, and added a 30% risk factor, divided for the number of days, and obtained a daily rate.

After one year, the customer proposed a sensibly higher rate, to align with my activities and what they were paying other consultants, and the same happened in following years, as the scope of my activities expanded.

Not really a good marketing manager, I would say- but I was lucky to have found a CEO (well, it wasnˇt the first time) who looked on a long-term perspective, i.e. building a long-term trust-based relationship (I was to support the company until 2006y).

But I saw this same mistake repeated by “consultants” working for government entities, supposedly helping startups, such as when a consultant said to a startup that I was supporting that a product that was sold for say, 100, should now be sold for 3+30%, because by industrializing the process the production costs (including recovery of the investment) moved from 40 to 3.

My reaction? If your existing customers absorb 100, keep 100, and save the margin to build a “war chest” to foster and finance innovation and maybe marketing in the future.

By reducing now the price, you will simply make your current source of new customers (it was a “niche” products for high spenders) feel cheated for having paid 100 something that you sell for 4.

And, if you look at the history of “cost plus” contracts (e.g. recently in post-War Iraq), usually companies inflate the costs.

Frankly, in my (limited) experience “cost plus” is applicable only to regulated and heavily audited industries and activities (have a look at UNIDO’s “Feasibility Studies”), or for joint-venture created to share services (I did also business plans on this issue), not to standard B2C (Business-to-Consumer) or B2B (Business-to-Business) transactions.

How did my rates evolve, once I learned the story (until I decided to stop being a consultant and relocate to Brussels)?

Well, moving from quantitative to qualitative consulting created a nightmare: to do it properly, you need to constantly review what you know, observe the market, study best practices, and experiment on new approaches (and not just read few articles and books and repackage the results of customers’ projects, as many companies do!).

Andersen in late 1980s boasted in a brochure of having 8% of the workforce in St Charles focused solely on knowledge collection and processing (and it was true); if you add post-mortem activities on projects, and other knowledge management activities, the real figure is around 12%-15% FTEs (Full-Time Equivalent) of the work force.

And if you reduce the size of the company, the share of non billable activities increases.

Therefore, after a short time almost at 100% (according to Milan Kubr’s “Management Consulting”, 210 days/year billable), I had to sensibly reduce my billable, using an higher rate for shorter term projects, as 25-50% was used to do experimental and pro-bono/network-wide projects, whose results were then fed to my network (and, from 2003, online in my e-zine), to keep the price justified (I received activities by word-of-mouth).

Unfortunately, I do not know any company in Europe that follows the same approach that was followed by 3M (as I keep reading and re-reading since 1990s) to feed innovation, i.e. allowing people to spend up to 25% of their time on “pet projects” (how the post-it came to life)- and also most fo the companies in my now dismantled network were focused solely on that unique, obsessive measure used by almost each company based on partnership: billable hours per person (what we called internally “the horse race”).

To summarize this unusual article-and-bibliography: I tried to use “standard” models to set prices and rates- but I never met anybody working for a large enough company who really used the “standard” model to manage the relationship between their company and their market(s).

Also the “optimization” models were really focused on optimizing internally, not on squeezing external suppliers or customers- as the CEO of a not-so-small company told me once: sometimes people in companies do something that they assume is the best interest of the company, such as postponing payments using whatever excuse they can, with the net result of upsetting suppliers- and making them less flexible when is needed.

Incidentally: of course, have a look at all the companies, books, articles I referred to.

As usual- any comment is welcome.

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