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Charting the course to data sharing


As the term would suggest, nobody can build a data ecosystem on their own. But finding the right path for shifting from an internal data focus to an external one is neither easy nor obvious. To succeed, a company needs a clear strategy for finding the right mix of governance, innovation, and partnerships. 

It’s essential that companies embark on this journey to stay relevant in a changing competitive landscape. In particular, younger consumers and employees are placing new demands on large companies such as disclosing things like their carbon footprint and social impact. At the same time, rapidly evolving marketplaces threaten to disrupt old business models yet also create big opportunities for new sources of revenue. 

This is complex because you are building deep data alliances and we all know that alliances are complicated, but you have to jump in, build trust and build new businesses together. It’s difficult. But if your other competitors scoop up all the allies before you, you won’t have any partners. So, we need to be in a hurry. 

The time to get started is now

According to a recent report by Capgemini, 48% of organizations surveyed said they are launching their first initiative on data sharing in 2021. In the next 3 years, 1 of 4 will invest more than $50 million in building their data ecosystems. Companies that continue to hesitate risk being left on the sidelines and missing the benefits of the virtuous cycle of sharing data. 

To get started, a company first needs to understand the value proposition, both for what a data ecosystem could bring to its business model but also what the company could bring to the table to benefit others. 

“Why would I share my data or my insights on how to build that new business model? Is my goal to attract more clients? Or to increase their loyalty? Can I do that by providing new insights regarding sales to partners or subcontractors? You have to clarify what is the business model.”

Take the case of a major partnership announced this year between healthcare giant Sanofi, Generali, Capgemini, and Orange. The companies created a joint venture to pool their data and technology to build a new health care platform. With emerging connected devices, the platform will allow for greater monitoring of things like diet management and exercise for diabetes patients. It’s a win for consumers, but also the partners who will deliver new services while also saving money in some cases. 

You can be connected to your insurance company all the time because diabetes is really expensive. If you are showing that you are taking care of yourself, you can decrease your cost of insurance.

Another example is Consumer Packaged Goods companies. Given changing consumer behavior, such companies are offering greater transparency into their supply chains – from raw materials to labor practices to environmental impact – to demonstrate that their products are responsible.  

In this case, the value lies in making the brand stronger to create greater loyalty, while also potentially providing data that help suppliers better manage costs. These suppliers could also benefit from greater insight into promotions or new brands to help them adjust stocks. 

For example, Coke has created a more robust data ecosystem with this bottling partners. The soft drink giant has started to share more insights into local sales with those bottlers which in turn has helped these partners make better decisions about what kind of packaging to use: bottles or cans? It also helps adjust storage and refrigeration needs which can vary with the size and shape of the containers. 

The objective is to allocate the right bottle to the right markets and to reduce massively the level of stocks and to optimize globally the performance of both Coke and their bottlers.

These choices on goals can help drive decisions about which segments of data to share. Having clearly articulated its motivations, a company must next take a hard look at its data maturity. How reliable is the data? Is it centralized? How is it managed? There is no fudging these answers and no quick fixes for issues that probably should have been addressed long ago. However, having a realistic view can help catalyze executives to take the necessary steps so their data can be in a position to be of value to potential partners. Mapping out plans for a data ecosystem can help shape the decisions that solve the data maturity questions. 

“The ecosystem will be a real challenge for some of our clients. Many of them remain super siloed. This will force them to increase their data maturity even if before they were not able to organize themselves.”

As momentum gathers and focus on needs increases, companies can start to identify the technology partners that will help them build an ecosystem. This represents an area of rapid innovation and disruption. Part of Capgemini’s role is to help vet and select vendors because the right partner for one company’s needs is not necessarily the right partner for another. It’s important to understand whether technology needs can be met by a plug-and-play solution or whether the situation demands a more customized approach. 

Next, executives must explicitly define the business model the cost structures and revenues. What is it going to cost to construct the data ecosystem? How many people will be dedicated to the project? How will the results be measured? 

It’s not necessarily money gained, but maybe you are getting insights for better performance or perspective. Maybe you are able to anticipate more because you have more information so there is impact on your operational efficiency and your competitiveness. That’s okay as long as everyone understand the definition of success.

Starting your Data Ecosystem journey

The question of governance must always be central. Partners need to trust each other, and that starts internally. Groups not accustomed to working together internally must be brought around the table to understand the motivations and intentions behind the project.  

It’s essential to create a foundation of trust within the company before the same confidence can be achieved with external partners. Fortunately, many of the emerging data technologies can help foster that sense of trust through their functionality. 

“You need to trust your partner before you share part of your assets with somebody else, a balanced relationship needs to be ensured at the beginning. You need very specific terms with those partners so nobody is worried about somebody stealing their golden nuggets.”

Finally, companies shouldn’t be overwhelmed the enormity of the stakes or the tasks that lie ahead. More important is to just dive in and take the first steps. While it’s important to have big ambitions, find a way to start with a more modest project that allows the organization to start learning and growing.  

You can’t spend 20 years studying something to make a plan. It’s better to take those first steps. Along the way, you absorb new competencies and attract new people. So think big, but start small.

Interesting read?

Have a look at our POV  to learn how to make the most of data collaboration business opportunities, gauge your organization’s digital maturity and determine where you should start your data ecosystems transformation journey.