As you may have noticed we have started a peer group process with leading firms from the Process Industries. These companies explore what comes after the obvious first steps in Digital Transformation which are operational excellence (smart plants with predictive maintenance and remote controlling, smart supply chains, increasing management capabilities via real-time insights into KPIs and improving the predictability of future business) are taken.

After several discussions we have found that anchor point for our discussions will be ‚Using Digital Transformation for catalyzing growth‘ – where the ‚growth platforms‘ may be coming from the market side and/or from the technological side.

Operational Excellence in the focus

In the Desktop Research that we do to support the peer group’s discussion process we have collected more than 200 studies and articles. Our first analysis showed that currently there is heavy focus on systematically exploiting the Operational Excellence benefits of Digital Transformation

There may be several reasons why this is so: By ist very nature, Process Industries have a large base of installed sensors and a huge volume of historic, operational data. So the Operational Excellence focus …

• is in many cases a straight-forward extension of existing infrastructure (e.g. connecting two pieces of assets via cloud, collecting data and applying Big Data analytics)
• pays a quick dividend for Digital Transformation (savings on operational costs impact directly EBIT)
• does not require a huge change in the digital mindset since existing units and processes are provided with better tools.

Digital Transformation for growth: 8 routes

Interestingly, as we have found in our Desktop Research, the first papers are coming up (e.g. the one HERE) that look beyond Operational Excellence and address the growth theme.

As of now, we have found 8 roads in which companies are exploring growth via Digital Transformation:

• Insight into market trends – Applying semantic Big Data on content on the web, contained in the market studies, in CRM systems show patterns
• Data Wraps / Data-as-a-service – Adding product and process data provides the opportunity to ‘guarantee’ a flawless production to B2B customers; Data may also be turned into sources of customer lock-in or sources of revenue
• ‚Application consulting 4.0‘ – Application engineers armed with deep information about materials and processes may provide a superior customer application consulting; This might be sold via the value proposition ‘helping you to gain production performance’
• Smart products, e.g. functional surfaces
• Cross-industry platform plays – Partnering with players from different industries e.g. in the ares of functional surfaces or functional foods
• Additive Manufacturing – May be speeding up development cycles e.g. by building reactors to simulate process properties or may be a source of revenue, e.g. by delivering custom devices using smart products
• ‚Substance development 4.0‘ – Using semantic Big Data analytics to conduct reverse engineering (from desired function to needed material) and/or using automated pattern recognition to screen molecules in material or in medical contexts
• Insight into technology trends – Using semantic Big Data analytics to explore technology trends, including other languages, e.g. Chinese