Why is the ecosystem strategy your most important strategy?

How accurate is the picture your company has of your clients? The answer depends on the depth of the data you have available and how capable you are in combining different data. The need for a data ecosystem comes from the need to see the big picture: the individual and their everyday lives as a whole.

Business woman and 2 men putting together pieces of a puzzle in front of a background showing digital connections around the world.

Organisations accumulate data through every business process and customer encounter. Traditionally, data is also stored in databases specific to certain business processes.

This data is then used to a varying degree and exclusively from the perspective of a single business area or unit. Such data gives an extremely one-sided picture, as illustrated by the below image.

A photograph almost completely covered with different kinds of data-blocks, i.e. "sales data" or "purchased data", showing only the left upper corner with some blonde hair, where "marketing data" has turned transparent.

We can see in this example that there is an individual hidden in the image. By simply breaking down the organisational silos of your company, and by integrating your databases to allow the combined data to be freely used for the needs of different business units, we already see a clearer picture:

More data-blocks, i.e. "service data" and "online data", turned transparent, revealing more of the photograph behind them: a part of a childs forehead, some patterned cloth and more blonde, curly hair.

Now we see the person is probably a child.

But even if the organisation brings together all its data, the picture of the end user and situation remains incomplete. No phenomenon, no individual, no issue is only ever linked to one organisation. As consumers, we use a wide range of services and live lives with many different facets. Our daily lives and what happens in them is unique and all-embracing.

Our lives are not organised into silos when visiting our corner shop, our bank, our gym or using public transport; we live our lives as a complete whole. Our needs and purchase decisions arise from this overall experience, not from fragmentary events.

The need for a data ecosystem comes from the need to see the big picture.

The need for a data ecosystem comes from the need to see the whole truth, the complete individual and their daily lives, all aspects of a phenomenon—the big picture. The more data sources we can combine, the more complete and accurate the image achieved.

Few organisations have access to all possible data, and there is also data that has never been gathered or is otherwise not available. Therefore, when planning your data ecosystem strategy, the most important thing is to identify which data, apart from our own data, is the most crucial, who has it and how can you gain access to it.

Sometimes the shared benefits are greater than the risks created by competition.

Data partnerships can even be made between competitors. Sometimes the shared benefits are greater than the risks created by competition. When a company starts to build business based on data, it is advisable to rethink your position in relation to your competitors and even who your competitors are. Your data partner may turn out to be someone quite surprising.

Even more data-blocks, i.e. "partner's data" and "location data" turned transparent, now showing in the photograph a child spooning food in his/hers mouth and a part of a coffee cup on the table. Blocks such as "missing data" or "competitor's data" still covering other parts of the photograph.

The key elements in risk management are privacy policies and agreeing between data partners on who owns the data, who has access to it and for what purpose, and how the revenues generated through that data are distributed. Risks can be controlled by opting for a suitable contract term and notice period.

It is wise to try out the partnership first and test the feasibility of the data. Data markets are still new, particularly in terms of online data, and its pricing may sometimes prove difficult.

The real value of data can be truly measured in actual business when you are able to measure whether or not the used data source is able to pay for itself.

In the above example, it is clear that using the data accumulated by a single unit within an organisation is all but useless. The picture becomes substantially clearer as soon as data from different units is combined and it already forms a foundation for conclusions: we see an individual who appears to be a child.

It is not necessary to access all existing data.

When this data and analysis is combined with the input from sources outside your own organisation, the accuracy of conclusions is even greater: it is a child who is eating whipped cream.

The organisation does not need to have access to all possible data. As we see in this example, approximately one half of the data sources add value to the picture, so it is not necessary to access all existing data.

What is the data ecosystem strategy for your company like?

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