Solo episode with Bruce Sinclair, the host of the show, discussing how smart digital can enable predictive maintenance for margin improvement and data-driven business models to increase the exit multiple.

In businesses where maintenance has a meaningful impact on margins, we can use artificial intelligence to predict when assets will fail in advance of any noticeable signs of a problem.  By using smart digital to prevent unplanned downtimes, we increase the company’s operational efficiency to improves its margins, for a relatively low investment in tech.

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.

In this episode, Bruce discusses:

• How margins are improved indirectly and directly.
• Using smart-tech-driven operational efficiency to improve margins.
• How to deploy predictive maintenance to minimize unplanned down times.
• The three different ways smart digital can increase the EBITDA multiple.
• The concept of data-driven business models and how they are created.
• The example of the power-by-the-hour business model developed by jet engine maker Bristol Siddeley and deployed by GE and others.

Related links you may find useful:

• Article 1: Margin Improvement with Predictive Maintenance 
• Article 2: Deploying Data-Driven Business Models for Multiple Expansion
• LinkedIn newsletter containing these and other articles
• Season 1:Related episodes 
• Season 2: Episodes and show notes
• Season 2 book: The Private Equity Digital Operating Partner
• Season 1 book: IoT Inc
• Training: Smart  digital transformation certification