As we all know data is an asset gaining more and more attention in companies. The reason is simple - it’s worth more than gold. Based on discussions with various companies understanding the data value chain is fundamental for proceeding at all. Of course, pretty much all digital business is nowadays more ecosystem and network-based.
Still, the data value chains and even supply chains exist. There’s just a shit load of more of them! In the data value chain data is first collected by measuring things or created by human input. Then it’s collected and processed. After that, it’s packaged for reuse, exchange, or sales in various formats and in various layers in the data ecosystems and related catalogs and marketplaces.
Read more below or watch the story as a video
Prepare for internal use
At the beginning of the data value chain aim is to understand what data we have, where it is, how it can be accessed, and then make it easily reusable by our own staff. This is the hard first step to take and make a simple catalog of data you have or have access to. The next question is so what? We have gigabytes of source data here and there. It’s partially customer-related, something is touching out processes and even development speed.
Involve business decision-making in the process
Before going any further you need to have a business reason to proceed. Well, it would not hurt to have such even before cataloging your data, but after this, it’s a must-have. At this point, your business development should be involved in the process even if you start enabling just easier reuse inside your company. Why? The reason is simple - you should treat all data as if it will be published for others to use outside your company borders. Just like you have done with APIs. Prepare for the future and have one similar process for all products and services regardless of initial publicity.
The gain is faster time to market
Now that you have business development involved they can see the opportunities and missing pieces more easily and early on. The business design people craft data product and data service candidates and test those in the closed data ecosystems and in public markets before pushing those to implementation. Given that the business people are involved - at least following - in the internal data product development, they have a better chance to get data monetized faster since the time to market span can be shorter.
The rise of closed data ecosystems
Ok, but what’s going to happen in the data value chain this year. What is the biggest change expected to happen? The gathering of data and storing it will continue in various formats. Companies start to move from optimizing processes and services with data-based decision-making to selling and sharing data-driven derivates. This is where I expect to see a significant change happen this year. Companies are adopting the data product concept and joining closed data ecosystems in which they share data as products. This is how API Economy progressed as well. The big bang of data monetization via marketplaces is not likelyto happen yet. Companies are not ready for that on a large enough scale. The same applies to advanced data derivates like customer-defined value cocreation dashboards (services) and data stories to mention a few. The traditional product-focused logic and mindset are still very much alive and putting service-dominant logic in the business around the data products is still emerging.
How should our company be organized?
But how should our organization prepare for the future? What kind of model to aim for? In the transition phase, it might make sense to leave internal data products lead in the hands of your data management team.
Anything above it going to public either in closed ecosystems or beyond is controlled by business design and management. They are the gatekeepers for anything going outside the company borders. Take a look at the illustration, give it a thought and contact us to engage in discussion.