Data Science Director
Digital technologies are transforming industry at all levels. Read what Giovanni Bavestrelli, Data Science Director at Tenova, has learned from his experience in the company.
For the past years throughout my journey of digital transformation, I have been involved in many decisions and have thus faced many dilemmas. Some of these dilemmas are obvious; anybody involved in digital transformation will experience them. Other trade-offs might be more specific to my interpretation.
Keep in mind that these are dilemmas, trade-offs or balancing acts, between two seemingly opposite concepts, and yet there is no absolute right or wrong positioning. More often, a blend of the two concepts will prove to be the right combination to bring the most value to your organization and clients. I cannot know where the right compromise is for you. However, I do believe that wherever you position yourself between the two concepts, it will have a significant impact on your company.
IoT and Sensors vs. Digital Strategy
When we started on our digital journey, we focused on individual technologies, mostly on Internet of Things (IoT) and sensors, launching several pilot projects. We soon realized that the transformation underway was bigger than any sum of individual technologies, and that we really needed a digital strategy that would affect the whole company. We then developed a strategy and built a team. Having an overall strategy was key to bringing awareness and focus.
Exciting Technologies vs. Customer Value
People like me get excited about technology, but focusing on the technologies themselves can be distracting. New technologies redefine what is possible, but what is possible is not necessarily useful. Maintaining focus on customer value will indicate the right direction to take. Nevertheless, keeping up with new technologies can give technicians an idea of tomorrow’s needs even when today’s customers cannot yet perceive them.
Return on Investment vs. Leap of Faith
In the initial phase of a big project, it is natural to set about predicting the potential return on investment. On our own digital transformation journey, we found this to be very challenging. We quickly became aware of how difficult it is to determine the return on investment with any reasonable accuracy. For instance, we do not yet know what price our customers will be willing to pay for completely new services. Despite this, we took a leap of faith and invested anyway.
Cost of Investing vs. Cost of Not Investing
A leap of faith may feel uncomfortable. It is easier to face, though, when you weigh the potential costs of not investing. By neglecting to explore the possible returns of a digital transformation, a company risks waking up late to discover its market has evaporated while it clung to old business models. In short, the winning strategy is to balance the cost of investing with that of not investing.
Culture vs. Operations
Companies quickly focus on changing operations, but a digital transformation is primarily a cultural evolution. People need to learn to think differently, share, collaborate, experiment and risk. I believe this is as much about humility, openness and generosity as it is about efficiency, processes and technology. You can copy processes and buy technologies, but there are no shortcuts when it comes to human growth. It takes commitment, effort and time.
Hard Metal vs. Software
Our company has a traditional engineering culture focused on the tangibles of mechanics, steel, machinery and plants. A digital transformation requires a flexible and novel way of thinking about solutions, similar to what is common practice in the software world. Think, for instance, of agile methodologies. These new approaches and a focus on software might feel uncomfortable at first, but the shift is necessary.
Predict and Control vs. Learn and Adapt
Another way in which corporate culture must evolve is by shifting from the management style of “predict and control” to that of “learn and adapt.” In today’s digital reality, we learn as we go, which requires us to adapt and change direction quickly as we apply new knowledge and correct mistakes. Agile iterative processes are useful for establishing discipline while also allowing flexibility.
Big Data vs. Good Data
There is a lot of talk around big data, but “big data” is really more data than many of us realize. We found that in our projects, the challenge was to find any reasonable amount of data. There is a lot we can do with good data even if it is not so much to warrant the use of a Hadoop cluster. Start with the data that you have or can find easily, gather experience and insight while analyzing it and modelling with it, and prepare to scale up later.
Do you want to read all 30 dilemmas?
Related technologies
Want to know more?
Get in touch with our experts on the subject
