Today, we think a little about where it would be worthwhile to start utilizing data in a company and where not. By considering this, it is easy to understand what impact it has in terms of learning, quick benefits, and positive visibility.
The first is that often data-driven business is being considered through new technologies (such as VR, AR, AI, ML, etc.) or modern innovations. There is nothing wrong with this premise but all of these new technologies and their application to support an existing business or build a new business require a lot of expertise. This competence and its requirements are new to the business and for most people in your organization. Thus, there is a higher threshold to succeed in an overall project, not to mention the speed of success. In addition, very rarely is there any certainty about experimenting with new technologies for their business benefits, and as a result, the value of the data to the company is often low.
Next on the list are global megatrends and industry-wide upheavals such as experientialism, circular economy, consumer habits, global challenges, or anything else where customers are willing to pay more. The many megatrends that apply to all industries are such difficult and large entities that fundamentally change many different things in your own company, business model or operational logic that the use of data and the whole project becomes large, demanding and time consuming. This is not a quick and agile way to capture the business value of data.
Next on the list is the sharing, selling, and exploitation of data in ecosystems or long value chains. The comprehensibility and feasibility of this is already starting to be close to being worth choosing among the first data implementations. However, often in ecosystems and long value chains, the data maturity of companies is very different and because of this there may not be a common understanding, quick solutions cannot be implemented and best practices are lacking, leading to budget overruns, numerous inefficient meetings and eventually loss of interest.
The easiest way of all is to simply start with your company’s own internal needs and direct customer requirements. You are familiar with the needs of your own business, industry, processes and customers. The use of data in these sites is easy to identify, business benefits are easy to evaluate and calculate, and the return on data-based value also has a positive impact on your reputation throughout the industry.
In conclusion, we put an end to tempting technology reflections or difficult-to-understand digital business opportunities if you want to get the most out of the value of your data fast (and so gain competitive advantage). Start where the fence is Lowest, learn how to leverage data to your own well-known value, and only then move on to more difficult opportunities. Once you’ve built a data culture and verified its value for a while, it’s easier to get resources and time for new investments as well.