Generally considered the longest of the value levers, multiple expansion can be influenced both indirectly and directly.  Revenue drivers and pricing optimization indirectly elevate the EBITDA multiple by producing growth.  Similarly, margin expansion by improving profitability, buy and builds by increasing company mass and debt management by throwing off more free cashflow, also indirectly raise the exit multiple.  Since I have discussed these value levers and drivers before, let’s look at to how to use smart digital to improve the exit multiple directly.

The first way to directly increase the multiple is from the digital rerate – a premium associated with being digital.  If a non-digital company is transformed into a fully digital company, its multiple comp would be that of a tech or software company.  Accordingly, a smart digital transformation rerates a company’s multiple commensurate with how digital they have become – the further along in the transformation, the greater the digital multiple bump.

Implementing the structural changes needed to produce digital products is the second way to directly grow the multiple.  The development of intangible assets such as proprietary IP and the establishment of a digital team to continue developing these assets fundamentally changes the nature of a non-digital company and as such, this progress is rewarded with a higher multiple at exit.

Here, I’ll focus on the third way to directly drive multiple expansion: the deployment of novel business models. The source of all smart digital value creation is proprietary data – the same type of data that has made Big Tech companies the most valuable companies.  But instead of capturing proprietary customer data, we capture proprietary monetization data upon which new business models can operate.  Capturing monetization data shows how customers make money with our product.  This profound capability enables us to price our products properly (the true definition of value-based pricing) and to create data-driven business models that better interface with the business models of our customers.  The better the fit, the lower the monetization friction.

A key to developing a new business model is to identify the right KPI to base it on.  A simple but illustrative example is the power-by-the-hour business model developed by jet engine maker Bristol Siddeley and deployed by GE and others.  The insight is, airline carriers don’t want the weight of jet engines on their balance sheets, instead they would rather just pay for power.  This service business model couples to the most important airline carrier KPI: miles flown per filled passenger seat.  To enable this, the proprietary monetization data collected by jet engine makers is engine-use time.  This proprietary monetization data results in a win-win for both parties.  The buyer only pays for the engine when it’s being used to make money, and the seller earns more by deploying a recurring business model.

Collecting proprietary monetization data enables the development of novel business models that until recently, were impossible to deploy.  Moving from one-and-done product sales to sales that recur to continuously generating revenue are rewarded by the next buyer paying a higher EBITDA multiple.

HOW IT’S DONE

Once the right KPI is identified, the product/service is instrumented (sensors are added) to collect the corresponding KPI data.  This data is transported by the internet of things over the OT network to the IT network to software running on a server hosted in a nearby data center (the cloud).  There, the price the customer pays is computed by inputting the newly arrived data into the business model.  The outputted price is then transported by the internet to the company’s billing system, hosted on a server in a different data center.

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