The Motivation: factor 9 in EBIT
We all know how different the productivity of teams can be. Tom DeMarco analyzed software development teams and identified teams who are a factor 3 more productive than average and teams who are a factor 3 less productive than average. In other words, he observed a span of a factor 9 (!) for different productivity.
This fact is not only observed in the field of software engineering but almost everywhere where knowledge workers are working. The more geographically distributed the teams are the more significant are the differences in their productivity.
Translated into money this means that even if you pay the same hourly rate for two different teams, one of them might be worth only 22€/h/person while the other one is worth 200€/h/person. Up to now I have not met any CEO or CFO who do not care, if their EBIT is a factor 9 less than possible.
The Invisible Value
A lot of research is done to analyze the reasons for different productivity and how to create values that improve the productivity. Most of those values are visible values like the implementation of processes and tools. On the other hand it is well-known that invisible values like trust relationships between (geographically distributed) teams members increase significantly the productivity.
The Research Questions
- Categorize invisible values in a company (e.g. trust culture, cross-divisional cooperation culture, culture of mutual respect, openness…).
- How to strategically evaluate which invisible values are most important for the company in the current situation?
- Strategies for establishing or leveraging those desired invisible values in a company.
- Invisible values are usually difficult to measure. However, what are the possible metrics – or at least measurable indicators – which help to demonstrate the progress?
See also: “Carrier Process for Cultural Change Management”
and “Due Diligence of Enterprise Culture”
Please, let me know if you are working in this field or if you plan to work in this field or if you know about already existing research in this field.
Some time ago I did some research about managing of complex systems. The results were published at the M.I.T. Europe Conference.
Neverthless, I am convinced that there is some important aspect missing in this research. The research concentrated to collect straight forward engineering methods, most of them are already known as state-of-the-art methods in software engineering.
We know that some people are better in managing complexity than others. I am convinced that you can observe these different skills in manageging complexity also if both would have exactly the same knowledge of the above mentioned straight forward engineering methods.
Some people have just these ingenious skills to handle complexity better than others.
The research question:
What are these “ingenious skills to handle complexity”? Why are some people better in manageing complexity than others – even if they have the same explicit knowledge? What kind of implicit or tacid knowledge do you need to be better?
Some ideas what could make a difference
- not to be afraid of complex systems (never having enough information to decide on a complete analyses of the information), take it as it is instead of trying to divide it in non-complex systems (which is per definition impossible)
- having the skill to sense behavior of the system (which other people do not see)
- having the skill to connect new obervations with old experiences on a unconscious bases and to derive decisions – what I call an experience based gut feeling.
Sounds quite esoteric. Nevertheless, I am convinced that research in this field would deliver non-esoteric results. The interviews which I did were solely with engineers as the focus of my research was managing complexity in complex technical systems. Now I would include also managers (or better: leaders) as interview partners. A large organization is also a complex system and these interview would add some different point of view.
Hints to existing research or own ideas or approaches are welcome!
If I like to buy another company (with mainly knowledge workers) I would be interested to know their productivity factor of their enterprise culture. I would pay more for a company with an enterprise culture which leads to a productivity of 200% (related to average companies) compared to a company with an enterprise culture which leads to a productivity of 50% (related to average companies).
This productivity potential due to the enterprise culture cannot be solely derived from commercial data, as the commercial situation of the company depends also on many other factors (e.g. their position in the market).
The question is:
- How can you measure the economic value of an Enterprise culture?
- How much would you pay more for a company depending on this metric?
- Is the productivity factor of an enterprise culture (at least in theory) a proper metric of the culture. Nevertheless, how do measure the productivity factor?
- People CMM might lead you to a set of indicators for an enterprise culture, but does not really measure the business impact of these indicators. Metrics like function points are solely focussing of resources input and function output of the current (or past) work, but do not evaluate the productivity potential of the employees if the market and therefore usually their kind of work changes. Is a combination of both the right answer?
- Could a knowledge networking and collaboration index be developed which is the right answer to my question?
- Trust is one of the most important productivity drivers. How can you measure the trust in a company?
Does trust pay off?
In this blog I am posting research questions which are of interest for me.
Feel free to
- comment them or to
- cite reasearch papers which are already dealing with this topic