Big Data, Smart Data, Data Producers, Digitalization, Analytics library, Machine learning, Industry 4.0, Internet of Things…
In the last decade, many new terms were coined and used widely in panel discussions and in the media. These terms are quite often used without clear definition, creating misleading interpretations and conclusions. One prominent example is the inflation of “Industry 4.0” panel discussions, which sometimes have very little to do with Internet of Things (IoT) devices and decentralized transmitted data but with increased “Industry 3.0” usage.
Following some of these discussions on data economy one could think that these are just new buzzwords which will disappear from the “real economy” without leaving a trace after just a few years, like other buzzwords did before. However, this view seems a little shortsighted. There are strong drivers behind the data economy that will at least lead to an accelerated evolution of economic change, new value chains and ecosystems.
Data from IoT devices (sensors, mobile phones, embedded chips, etc.) and data from websites, social media, business transactions and the like, in combination with smart algorithms and corresponding software are a technological push factor for this development. In a data-driven society like ours they create economic value and new business models because sensors, processing, smartphones, and wireless coverage are readily available and at reasonable cost.
One simple example is the usage of data analytics in marketing and in sales. In the 1990s smart consultants used Excel spread sheets and pivot tables to impress marketing and sales directors. In 2018, such dinosaur methods no longer impress. The analyzation of customer data, of the customer’s reaction to different products and price levels using smart algorithms, which are often self-teaching, and software has enabled marketing and sales divisions to reach a completely different level of accuracy in predicting and targeting customer behavior.
Another example is the usage of algorithms and data in the production process. Individualization and widely differentiated demands of clients and customers have led to a much stronger variation of products. It is impossible to produce variations of cars or even cranes without product configurators and the corresponding algorithms.
Condition based monitoring can nowadays be done much more efficiently, when dozens of sensors measure the condition of a turbine, an engine, a compressor or a fan. The potential cost savings compared to periodical maintenance are enormous.
These are just a few examples, but many more come to mind: Usage of data collected from humans (blood pressure, heart rate, etc.) or measuring environmental data for utilizing the maximum energy for a solar park.
A short side step: Not every development is positive; one must only think of the recent misuse of personal data for election campaigns and the creation of new monopolies. The regulations of the European Union at times unfortunately appear too bureaucratic and not very helpful in addressing these issues.
Recruiting efforts of companies to find data analytic experts and similar professionals have risen significantly in the last couple of years. Moreover, universities have created and developed data science or data analytical curricula, another sign that we are observing a strong trend, not a straw fire. Internet and social media giants as well as “data-driven” startups are on people’s minds but for traditional companies the growing data economy is equally important.
For Chief Executives it is obvious that they must, together with their teams, define or re-define the company’s role in the data economy. An important pre-condition for a successful strategy and its implementation is to engage a strong data science team. Leaders and experts are the driving force behind the right innovations inside an organization. The key to successful business models is apt professionals working at all levels, driving the process. The revolution has just started, and we will see more of these developments within the next couple of years. Chief Executives and HR directors must be at the forefront of these developments, not late bloomers.