In The Adventure of the Golden Oak, Sherlock Holmes expresses himself thus: “Data! Datas ! I can’t make bricks without clay! “. At a time when we are barely emerging from the pandemic, many companies could say the same thing, as data is at the heart of their reinvention. Monetizing your data consists of making it available to external organizations, so that they can derive value from it. You still have to know where to start. Here are the 5 key steps to success.
Data at the heart of business reinvention
To rebuild and grow in a wildly changing post-Covid environment, businesses need to take a deep dive into the data related to their operations. Many organizations are already committed to monetizing their data. They explain their decision as follows: “Previously, we had a data strategy. Now our strategy is data.” Quite logically, this new paradigm requires considering data as an asset – we have already heard this – but also as a product. In this perspective, data can be exchanged for value, internally or externally. Frequently cited McKinsey* study estimates data collaboration generates $3 trillion annually. You still have to know where to start.
- Define data sources or domains
Many questions arise regarding the type of data to be used. Often, the first instinct is to seek advice from the teams concerned internally, Business Intelligence (BI) analysts, most often, or Data-scientists. Now it’s about building with them. The first step is to talk with business stakeholders to get an idea of what data sources or “domains” of data might be of interest. “Customer” data comes from multiple sources and includes for example customer profiles, transaction data or contact center logs. “Product” data may include, but is not limited to, production data, launch data, sales and returns or defects. The teams in charge of the data are familiar with the data they have. However, they don’t always have a clear idea of the scope of potential use cases.
- Identify potential uses
Who would be interested in this data? The best place to start is to ask how these are already being used, both internally and externally, and then see if other organizations could use them in the same way. For example, telecom operators scrutinize network traffic density in cities to determine where to place outlets. But retailers, developers and urban planners can also use this data to choose sites. We can also imagine a related use: a manufacturer of jet engines that exploits data relating to flight operations to improve its future products.. Airlines can also use flight operations data to improve their efficiency.
- Determine the best format
For data to be marketable, a developer or data scientist must be able to do something with it. For example, he can transform raw or enriched data into an application or an analytical model. This type of format is perfect for providing information to customers directly, within the workflow itself. They can thus quickly make a decision or act. At the house of PepsiCothe data team created an internal product, ROI-Engine.** Aggregating data from over 60 sources, the app determines which marketing or advertising campaigns performed well and how to refine them. To ensure that marketed data is up-to-date, direct, real-time sharing is always a better option than copying and uploading or uploading files. Custom interfaces can also provide ease of access and use.
- Measure the value of offers using an agile approach
Working directly with a customer or partner helps measure the additional value gained through the use of data. For example, if new data identifies specific targets and thus helps a marketing campaign to increase conversion rates, then some of this increase can be attributed to the data. In all examples, it’s about taking an agile approach to testing new data offerings and determining the value they provide. Ultimately, the market will determine the price.
- Find the right marketing channels
When it comes to marketing, many consultancies and service providers help guide businesses through this process. In addition, the emergence of data marketplaces facilitates the discovery and access to data. Instagram, for example, shares shopping trends with its retail and CPG customers. This marketplace has more than 500 million products in its catalog, from more than 40,000 stores, in more than 5,500 cities.
To monetize it, organizations just need to have data that can bring value to other businesses. Some of them, such as GE Aviation or Siemens Mobility – manufacturers of aircraft engines and locomotives – have understood this well. They now offer data products and services even though this is not their main activity. Through the monetization of their data, many companies have a wealth of unique opportunities to reinvent themselves and grow… Provided you follow these five steps.
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