The cautious process to data driven change (2): data autonomy as the guiding principle
More and more, data is used as an important asset and means to improve value chains and make the traceability of supply easier. This has made it an essential element of our work; with many companies we work on the setup or improvement of what we call a Management Information System (MIS): a system of collecting, storing, analysing and using data. Setting up such a system is a complex process and there are many aspects in the design and roll-out of the system that can affect success, quality and in the end sustainability of the system. In this blog series we discuss three aspects that can make or break the set-up of a successful data system. In the first blog we elaborated on the importance of making data insightful so every actor in the chain realises that in fact he collects and uses data for himself and the improvement of his product and business, which is vital for the data quality along the chain. In this second blog, we focus on our observation that, when working with actors in the supply chain, a proper embedding of answers to ownership and privacy/security questions are essential to make a MIS work. Data is power and, thus, sensitive. In the third and last blog that is to follow, we will discuss the importance of having flexible systems that can complement existing systems that value chain actors are using to have the biggest impact.
The main trigger of the collection and sharing of data in the agricultural supply chains we work with is often the traceability of the goods. (Mainly) Western final markets want to know where the products they buy are coming from and whether the premium they pay for really ends up in the hands of the farmers. To make this happen, it automatically means that data is flowing through the whole chain, from farmer to the final buyer. At the same time, as we mentioned in the first blog, the sharing of data may provide insight in the productivity of its suppliers and can be used for tailor-made improvements. With so much data being shared, questions that are becoming relevant are: what is exactly shared? Who does own the data? Who can access what? And to what extent?
Data is power
Where data is collected, there are questions about rights, ownership and accessibility. In that sense, an average European is no different from a farmer residing in Africa. You can choose to give your data away to get, for example, personalised adds or support back. When in a business relationship, however, the more data you provide, the more your bargaining position may be affected. Simply, because data is power. And this also holds for all value chain actors. A few examples to illustrate it:
For farmers it may not always be in their own interest to share (all) their data. When, for example, their buyer has all the performance data, the buyer knows the share that is sold to him, which may affect is bargaining power or freedom to run his own business as he wants. Another example is that farmer (organisations) do not always know where their data goes to or who will see it. What we even experience is that organisations indicate that they, after submitting data, have no access to it and they have no idea where their data is stored. They simply enter the data into a black box. And we see that this affects the willingness to share (real) data. In one case, for example, we experienced that farmers provided wrong figures on purpose. Their reasoning was that if they provided bad figures, they would receive more support. Or that in case they provided good figures, they would be selected for special programmes and projects.
Although the fact that legislation on data collection is also becoming more strict in various African countries, the core message of this blog is that handling the data of the actors in your supply chain with care is also in your own interest. It is about loyalty, data quality and if combined with our suggestion in blog 1 to help them make data insightful, it may even be about the quality and the quantity of the products. And, thus, about the success of the MIS. Because of this, if we are working on an MIS, we work with the following ground rule: people need to own their data, also after submission, and have the ability to decide what they want to share and what not. In other words: data autonomy. This needs to be reflected in the way the MIS is build and in the contractual arrangements between the parties. Only in this way, farmers, organisations and companies in the supply chain will be taken along in such a way that an MIS is not a burden, but also a chance.
In this blog series we zoom in on three aspects of an MIS that may be key for its ultimate success. In blog three we will look at the flexibility of an MIS to link with other existing systems.
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