For many, digital transformation –the topic we discussed in our previous article– comes hand in hand with the idea that it is something you buy outside the company and then bring into it. And, voilà! Everything is resolved. 

The reality, however, proves otherwise: digital transformation is a process that comes out of the organization’s core, of its firm resolve to carry it forward and capitalize on the abundance of data distributed in the files, experiences, and memories of those who are a part of it. This is particularly true in medium-sized companies. The great majority of companies in this segment that have been active in the market for many years have one thing in common: they all have accumulated a considerable amount of data over the years. However, in general terms, the data reside in not centralized repositories. Additionally, it is unlikely that those companies will have the tools to transform the data into insights to optimize decision-making and improve business performance.

The problems and difficulties of this situation cannot be solved merely by “buying technology.” Quite the contrary. The first step is to identify the business needs and perspectives of the organization and answer the following questions: “In what aspects can I outdo my competitors?” “How can I improve my clients’ experience?”, and “In what new markets can I participate with innovative –or even disruptive– proposals?”. Once we have developed the strategic vision, we can decide what data technology investment to turn those initiatives into something tangible.

Despite the temptation to move ahead rapidly toward the stars of the moment –such as artificial intelligence or big data applications–to get results, we will first have to roll up our sleeves and move toward less glamorous, though fundamental, tasks. They include verifying data integrity and quality, integrating data in shared repositories or detecting duplicate, hidden or erroneous data, and finding the tools to process and analyze them in an understandable format. After those tasks have been performed, we will be able to link the strategy to the data, understand the company’s data capital, and discover ways to turn them into value for the business.

The journey toward the data-driven model

The starting point of this journey is a diagnosis of the current situation: analyzing the condition of the structured processes and the use of data, leveraging through the use of richer data to improve the business as it is now, accessing other segments, adding new clients, improving costs, optimizing operations or reducing risks. It is necessary to create an inventory of data assets, link them to a well-defined strategy, and analyze if information gaps need to be filled.

This prior research is fundamental. At Making Sense, we call it discovery. It is one of the processes that make us different. We believe that the crucial first step to launch any project is an analysis conducted by experts in technology, business, and design who will generate business with a forward-looking approach. Market experience and knowledge of the trends in the sector are essential. They may offer the client`s knowledge about data tools and expertise, particularly in the use cases that we can access as technology partners.

The profound change is cultural. Some components of the decision-making process are excluded, such as intuition or experience. This often leads to biased views and conclusions drawn from a limited-scope perspective. Those components that have been excluded are replaced by data-driven knowledge. This model is widespread in different countries. According to a survey published by Statista, 77% of the organizations in the US that responded to the survey have confirmed that they have used the data-driven decision-making model. In Germany and the United Kingdom, 7 out of every ten organizations have done the same. 

Practical steps toward monetization

Data monetization possibilities are as vast as the company’s creativity allows.

Once you know the number of data assets you have, it is time to identify use cases, the level of competitiveness, and the availability of alternatives to what is being proposed to define new data-driven products and services. The focus should always be on who the potential client is and how willing it would be to use this service. We must think with an open mind, without obstacles in the way. For instance, we have to evaluate what external data we could combine to increase the proposal’s value. Is there a process at present that makes it difficult or even impossible to manage data well? Can data optimize the client’s experience in any way? The answer to questions like these can be a fundamental guide to moving forward with the initiative.

The road toward monetization is not limited to a good idea. We must also develop the distribution and sales strategy needed to support the initiative and generate a clearly-defined roadmap of how these new data products will go live to be used by clients.

The benefits of being data-driven

The old data systems based on silos, manual analyses, and spreadsheets are highly prone to errors, hinder the optimum performance of processes and obstruct the capacity to develop data-driven products and services to compete in the digital economy. 

Having data assets that guide corporate decisions in real-time makes it possible to focus on the right priorities, define new business models to monetize the data, and, additionally, achieve a level of transparency that generates a more significant commitment both by collaborators and clients. 

Suppose the company seeks contributions from a PE. In that case, the investor can concentrate on the performance metrics that impact the company’s value and potential without biased views or hidden or overlooked data.

The data are available. The possibilities to generate value are limitless. Moving ahead based on those possibilities makes the difference between getting stuck in the present until obsolescence sets in or entering the future business world head-on.

Only after these improvements have been implemented can we start thinking about innovation and incorporating new ways of creating and developing business processes that are profitable and sustainable in time, in line with the company’s future vision.

We should not forget that a survey by NewVantage concludes that the main challenge to being a data-driven company is not technology per se, but people, business processes, and culture (92.2%). The company’s leaders and its team will be as important as all the other aspects we have mentioned.