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Contenu fourni par Bruce Sinclair. Tout le contenu du podcast, y compris les épisodes, les graphiques et les descriptions de podcast, est téléchargé et fourni directement par Bruce Sinclair ou son partenaire de plateforme de podcast. Si vous pensez que quelqu'un utilise votre œuvre protégée sans votre autorisation, vous pouvez suivre le processus décrit ici https://fr.player.fm/legal.
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Improving Margins and the Exit Multiple with Smart Tech In PE

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Manage episode 362934633 series 1316969
Contenu fourni par Bruce Sinclair. Tout le contenu du podcast, y compris les épisodes, les graphiques et les descriptions de podcast, est téléchargé et fourni directement par Bruce Sinclair ou son partenaire de plateforme de podcast. Si vous pensez que quelqu'un utilise votre œuvre protégée sans votre autorisation, vous pouvez suivre le processus décrit ici https://fr.player.fm/legal.

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:

  continue reading

141 episodes

Artwork
iconPartager
 
Manage episode 362934633 series 1316969
Contenu fourni par Bruce Sinclair. Tout le contenu du podcast, y compris les épisodes, les graphiques et les descriptions de podcast, est téléchargé et fourni directement par Bruce Sinclair ou son partenaire de plateforme de podcast. Si vous pensez que quelqu'un utilise votre œuvre protégée sans votre autorisation, vous pouvez suivre le processus décrit ici https://fr.player.fm/legal.

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:

  continue reading

141 episodes

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