Figure out whether the essential nature of the business lends itself to analytic understanding… if so, and if your management team is sufficiently broad-minded, the benefits can be far-ranging.
We recently built a realistic simulation of a services business. The original purpose of doing so was to test the cost and quality performance of different operating model re-designs. We were however fortunate enough to be working with an open-minded client management team – highly collaborative amongst itself – that could see the potential for much wider benefits.
Some business are just made for analytic understanding – typically those with reasonably high volumes of activity (where “activity” can mean almost anything: customer interactions, operations throughput, recruiting activity, etc.). Logistics businesses are just one example.
If your business is one-such, a new – much more robust – way of doing operating model design (e.g., determining the optimal number, location, organisational model, skillsets of logistics staff) is to build a realistic simulator of the business operations and test – quantitatively – how well each design alternative performs in simulation. Not only can the best performing be selected, but one gains an ex-ante understanding of the post-implementation business performance metrics. This may not be new news to the very largest operations-intensive businesses, but such techniques are now readily available to organisations of all sizes.
Hang on though. We now have a realistic simulation of the business. Guess what? This can now usefully inform HR decisions (e.g., what number of employees, with what skills in which locations; what optimal role / skill redefinitions?), commercial decisions (e.g., what are the delivery economics of new B2B contracts and hence what should our contract pricing be?) and growth strategy (e.g., which new geographies have attractive underlying demand characteristics for us to go after organically and/or inorganically?). Our client realised just that so that now, what began life as a tool to support a one-off design exercise, has now become (with a little development) a core strategic decision support tool which provides management with insight for a wide range of decisions.
Incidentally, a key aspect of the tool is its visualisation interface. In a later newsletter we’ll showcase how some of the newer visualisation tools allow businesses to go beyond merely viewing static portrayals of existing datasets, to interactively test and visualise different business scenarios and decision implications.