As we have pointed out in earlier posts we are forming a peer group process with Process Industries VPs from Innovation, Marketing and Sales within larger companies: “Digital Transformation – What it really means at the VP level”.
Companies from Chemicals, Paints, Health&Nutrition, Oils&Additives, Food, Dairy, Beverage and Life Science industries are lining up for participation – which we think indicates the timeliness and relevance of this issue. Please see the end of this post with details of how to join the peer group.
One of the first things we did to design this process was to come up with an actionable, business-centric definition of the term “Digital Transformation”.
We are now working on the detailed methodology to support discussion about where Digital is relevant for a company’s business model. We have chosen a “picture of the future” approach: A systematic process in which we assess opportunities and threats to business models that come with deploying the IT tools that make up digital disruption / digital transformation.
Digital Disruption and the Digital Business Model Canvas
Digital Disruption could mean massive competitive advantage using state-of-the-art IT tools.
But it could also mean destruction of a company’s business model.
Seen in that way, Digital Transformation brings an opportunity for extraordinary focus in new thinking – both in operational excellence as well as in innovation – to envision and to implement digital disruptions.
But how does one start in thinking about these disruptions?
The business model canvas developed by Alexander Osterwalder and others has become the de-facto standard in many companies for describing business models.
But it has some shortcomings. It’s is not very handy in developing new business models and in testing potential new business models. Furthermore, it does not bring in the the competitive perspective. For this reason, the Lean Start-up school of thinking suggests taking an iterative process focused on subsequent validation of the elements of the business model canvas.
But at the end of the day, the business model canvas is a good starting point.
In the Digital context we need to extend the business model canvas through four additional elements:
- Customer‘s customers and their business models: A big value point in using state-of-the-art IT tools (see below, the “Digital Disruptors”) is that they allow for cross- industry / cross value-chain integration. Designing integrated business scenarios for the company’s customers without having their customers in focus will be hard.
- Upstream players and their business models: This is the same argument but applied at earlier stages of the company’s / the industry’s value chain.
- Ecosystem: In most Digital Transformation scenarios, value creation happens within an ecosystem with multi-directional value and service streams across the various stakeholders involved (e.g., partners, customers, users – maybe even with competitors, e.g. by sharing industry data). It is necessary to obtain a holistic view on all relevant stakeholders and their contributions in order to maximize value . Therefore, it is important to shift the focus from the company to the ecosystem level when defining the business logic. Case in point: In most of our projects we have found that the a linear value flow from suppliers and partners to the customers (which implicitly is assumed in the classic business model canvas) does not apply: Rather, the value created in Digital scenarios comes from sequenced, looped flows of data and physical goods and/or services.
- Data / IP Management / Risk Management: As Digital Transformation scenarios capture a lot of data, a structured approach is to be applied when defining how to leverage that data (either as value adding services within the same business model or in subsequent business models). This might include direct data monetization or other means of reusing information as assets in business models. Furthermore, Digital Transformation scenarios pose new risks (e.g. cybersecurity) and new challenges: Who owns data, algorithms, decisions etc. that come out of digital business models? And how is risk managed in cross-company / cross-value-chain scenarios?
Digital Transformation: Meet the Digital Disruptors
The competitive weapons of the Digital Disruptor can be summarized in four categories:
- Mobile (including Wearable Devices and Augmented Reality): Business these days is “on the go”. You’d expect to have your business information at your fingertips on your smartphone. In some scenarios, wearable devices and/or augmented reality play key roles. (Note: Of course, wearable devices may also be seen as part of the Internet Of Things, see below, but we have put them here since in most scenarios the mobility aspect is paramount).
- Cloud: Public and private clouds allow for virtual integration of data from market players. Some companies such as General Electric or Bosch are building cloud infrastructures that not only provide data storage but also a marketplace of analytical applications and access to anonymized data form other market participants.
- Internet Of Things (including Additive Manufacturing such as e.g. 3D-Printing, RFID, etc.): In many future business scenarios, “things” such as cars, refrigerators or valves will monitor their own and environmental conditions on their own and communicate with other things (such as e.g. the traffic control systems or other things in the factory process) directly and provide some sort of self-management. When problems arise, these devices can alarm human experts who then take timely action.
- Big Data analytics: Modern software tools such as SAP HANA, IBM Watson or Hadoop allow for blazingly fast analysis of structured or unstructured data and to elicit patterns such as trends or white spots in patent landscapes.
Painting “Pictures of the Future”
Applying the Digital Disruptors onto the Digital Business Model Canvas can be used to systematically generate a long list of potential digital disruptions. Four examples may illustrate our argument:
- GSK is using wearable devices to monitor patient compliance and patient condition in clinical trials (“Customer” / “Mobile”).
- BASF is providing farmers with detailed suggestions on which fertilizer to use for which part of the crop, depending on crop data, soil properties and weather data (“Value Proposition” / “Big Data”).
- Kaeser is increasingly shifting its business from selling compressors to selling pressurized air on demand. The compressors are remotely monitored and intelligent preventive maintenance applied: Service units are sent out not in defined intervals but when problems are likely to occur. Using the data collected, Kaeser is also advising its clients how to optimize their production processes (“Value Proposition”, “Delivery Channel” and “Revenue streams” / “Internet of Things” and “Big Data”).
- One of our clients from the aluminium industry integrated its quality management (QM) system with the QM system of an Automotive OEM. By extending the base of quality-relevant parameters, the overall quality was increased and a project ROI of 3 months (!) was achieved. (”Customers”, “Value Proposition” / “Cloud”, “Big Data”).