How to get started with digital transformation
Digitalization has been recognized as a key driver of business evolution across industries, and as a result, on the strategic agenda of all major companies. But where do you begin?
Digitalization has already redefined many traditional B2C markets and enabled rivalry from unexpected industries. We have all heard how Uber and Airbnb have disrupted the automotive and hospitality industry, respectively (perhaps after this we could all agree to start using new examples of disruption). Usually when we talk about digital disruption, we tend to think B2C. Perhaps because B2B context can be harder to grasp, or maybe it is rooted in the fact that we have all had experiences on the B2C front and can relate to Uber and Airbnb.
But what about B2B? This major paradigm shift is also taking place in B2B, enabling opportunities to create and capture value through new digitally enhanced or enabled business models.
Despite being in its early phases, many believe digitalization in a B2B context will have much broader and groundbreaking effects across several industries.
We usually talk about two kinds of opportunities: ones that increase efficiency and ones that create growth. In practice, these can, and most usually do, overlap one another.
If we look at the changes digitalization has enabled to date in terms of monetary and time savings in processes such as production and maintenance, we can only imagine the opportunities advanced analytics, automation and AI will create in the future. To give you some examples, Altum Technologies (winner of Slush 100, 2017) pitched their solution that enables big industrial companies to clean their equipment automatically without having to stop productions, take apart machines or use manual labor. Another example is Konecranes’ preventive maintenance* that helps identify risks and improvement opportunities and guide decision making to optimize operations.
Robot Process automation not only reduces process duration and costs, but also makes process more easily integrated and scalable. Combining automated processes and forming partnerships or ecosystems that reach beyond one’s company increases resource and asset efficiency even further. It gives companies access to totally new resources quickly and at low cost while spreading out the risk among several players.
For most, this is the more interesting category – but also the more challenging of the two. Creating new business models requires companies to proactively shape both market definitions as well as industry practices and mindsets. This begins with widening the view of what value is for different stakeholders and redefining markets and ecosystems. A great example of this is KONE’s concept Residential Flow that clearly puts the customers’ everyday needs in focus and defines their market accordingly, instead of focusing on industry or product boundaries.
Digitalization has brought customer excellence and co-creation to a new level by enabling companies to connect with their customers and other actors at a far faster frequency than before and throughout their entire life-cycle. Think for example about how user data can be collected, combined and analyzed in real time to gain insight and develop new value propositions that truly benefit customer needs even integrating one’s business processes and tools with the customers’.
This also gives companies a much deeper and far more accurate understanding of different customer segments and how to develop mass-customized value propositions for each segments’ specific needs. A case we often refer to is Kalmar Insight that is turning data in to new business with clear separate value propositions for Operations Management (real-time productivity and operational optimization), Maintenance Management (collaborative operational planning and fleet availability), Health and Safety Officers (easy incident, accident and machine event overview), and Senior Management (long term productivity and cost trends)
Where to begin?
It is no wonder that digitalization has been recognized as a key driver of business evolution across industries, and as a result, on the strategic agenda of all major companies. But where do you begin? Companies are typically puzzled by questions such as:
- What kind of business model would be most profitable?
- What kind of capabilities would support creating and capturing the most value?
- How to organize to cap on capabilities and resources internally and externally?
- How to get the transformation started?
Digital transformation as a topic is both equally broad as it is deep. We have found that the key to getting started is breaking it down into themes, utilizing various framework and tools along the way and flexibly learning and adapting accordingly.
As digitalization enables and emphasizes co-creation and sharing of resources, blurring the lines between different stakeholders, we encourage organizations to start with an outside-in approach:
- Innovating for growth by challenging and redefining current market definitions and taking an ecosystem approach to innovating winning customer value propositions and new types of earning logic for different customer segments.
- Achieving growth by analyzing and developing your business model based on quick piloting and data to support a holistic customer experience in the most effective and efficient way.
- Driving digital transformation by assessing your organizations digital maturity, creating a purpose driven digital agenda and systematically encouraging a supporting transparent culture, agile way of working and data-driven decision-making.
Digital transformation is a non-linear process where different phases and steps can, and most likely occur simultaneously. However, these steps can help provide a structured approach to both getting started and driving digital transformation in a systematic and iterative manner. Think of Version 1.0, regardless of what you do, will always be a guestimate to create a reaction, gather data, learn and adapt.
* The difference between preventive (PM) and predictive (PDM) maintenance? The first is done on downtime, while the latter is done as the machine is running.