PEOPLE | Jul 13, 2017

The datum? Only one piece of a complex puzzle

Interview with Luigi Geppert on the relationship between data and strategic planning

Paying attention only to data is not sufficient as a key to development for companies,
according to Luigi Geppert, Professor of Dynamic Systems and Business Strategies at the Catholic University of the Sacred Heart of Milan and senior partner in Fair Dynamics Consulting of the Engineering Group. Data certainly play a fundamental role, but just collecting and analyzing them, without using them in a wider strategic vision process, does not give much value.

In fact, argues Geppert, the biggest risk for businesses of all sizes is focusing on data and analytics tools, often also “because of trend-driven needs” without following a process of transformation that takes strategic pathways rather than technologies into account.

Data are indispensable for preparing an ideal environment for understanding the complex problems that companies usually have. Through the information I gather and analyze, I can understand if the organization is correct and consistent, check business process, and especially if there is alignment with business strategy. Companies have non-trivial contexts, with socioeconomic and financial constraints, where mere reading of a datum, even though it represents a backbone infrastructure, contributes little to identification of the actions necessary for improvement.

So, how can data be used in the best possible?

Today, data analysis techniques exist that are really sophisticated and are a necessary but not sufficient condition for strategic analysis. What is needed is certainly to start from the collection of data, from their cleansing and analysis to reach the phase of processing through techniques of simulation modelling, simulations of the future from a strategic point of view. The no datum, no party idea is thus only partly true because having the datum just for having the datum does not help.

If we talk about ERP?

In the 1990s, many companies put themselves in the hands of ERP, incorrectly thinking of them as strategic simulation tools. Nowadays, relying on these is a mistake because the tools are not flexible and are very often based on business rules introduced many (too many) years ago, which have never been revisited and thus no longer valid and which the company frequently no longer even remembers. In this way, the risk is being dominated by software rather than benefiting from it. Medium to long-term simulation is what is needed if industrial, economic and financial risk is taken into account. What is usually done is to proceed to using particular indicators and, above all, fielding teams with different skills, given that, as we said earlier, corporate contexts are always very complex and certainly not linear.

Any good example of strategic use of data?

There are really many examples. Among these we can mention a case history in the railway transport sector on which we worked. It involved the engineering body of a railway management company and the aim was to verify the possibility of extending the installation of real-time diagnostic systems capable of improving the maintenance process to some trains. To demonstrate the convenience of this operation, thanks to a specific simulation technique we implemented, two different scenarios are compared: the first that simulates the collection of diagnostic data and therefore a maintenance policy under condition; the second that reproduces the current situation of a classic periodic preventive maintenance policy. Through this tool, it will be possible to make the best decision and concretely demonstrate how the costs to be borne for the installation of advanced diagnostic systems can widely compensate for the unavailability of trains.

Another field of application, again linked to the transport sector, is where we developed a strategic model useful for identifying how to rationalize handling activities in airports (that is, the support services for airlines and passengers that often lead structures into a situation of loss) and how to develop and strengthen those not linked to aviation, namely those related to commercial and retail services, to provide new lifeblood for airport facilities. The business model for airports, in particular following deregulation, has in fact changed, and if structures want not only to survive but also make a profit, they have to focus on collateral activities such as in the commercial sector. However, to do this, and thus decide on any investments in infrastructure or acquisition of financial resources, a tool is necessary for simulating future scenarios and enabling understanding of how the entire business ecosystem is modified by changing some variables.

A final, very particular, example concerns the pharmaceutical companies for which we have developed a model that can simulate clinical tests on virtual patients through data-based simulation modeling techniques. A tool that has scientific value not only in the clinical trial phase of the drug but also in the post-market product support phase.

What skills are needed to make the most of data?

To create simulation tools such as those described, you need to have teams with different skills. IT technicians are not sufficient, as might be believed. You need biologists, mathematicians, physicists, psychologists, economists…

Sonia Montegiove