The cautious process to data driven change (3): Flexibility of systems

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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 the second blog, we focussed 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 Management Information System work. Data is power and, thus, sensitive. We will finalise the blog series with the third attention point: can a system interact in a constructive way with other systems of users themselves? This makes the difference for speed, efficiency and accuracy with which a Management Information System is adopted, and whether a system can have an impact beyond its own value chain.

When working with actors in the supply chain, we observe the importance of having a system that is not standalone, but can interact or be fed by other systems. To start with an illustration: generally speaking, farmers in West Africa grow various crops to spread their risk and have food and income whole year round. This automatically implies that they are part of multiple value chains. Decisions they make for one crop may influence the production of other crops; if one wants to grow more rice, this may be at the expense of the number of pineapples that one can produce. And one can invest in fertiliser, but it can only be applied once. As such, the farmer reality is a complex one in which every year decisions are taken based on assumptions about the needs and possibilities for that year.

At the moment, more and more buyers invest in digitalisation and data collection in their supply chain to gain insights and improve traceability. Most of the time, and logically, these data systems are first and foremost geared towards their supply chain only. It involves, however, some risks, or put differently, does not capitalise on opportunities that are also there. Let’s name two:

Inefficiency of various systems

We see producer organisations that are asked by buyers to use their system for data collection. When selling four different commodities, as a farmer (cooperative) it is, therefore, not uncommon to have four separate apps or systems to work with to capture all the data for the four buyers. This also implies the four fold registration of certain data, because all buyers will need the basic data of the farmers. On top of that, the entered data is not always accessible for farmer cooperatives, so they often keep their own system as well, which makes the data collection double work at all.

Inability to learn and improve

If data of different crops is collected and stored separately, with own traceability codes per value chain, it often implies that data of different value chains is not analysed and used all together. This means a missed opportunity for cross-crop analysis, which could lead to holistic analyses leading to insights, deliberate business decisions and optimisations on the farm. Besides being a missed chance for farmers, this is also a missed chance for off takers: in earlier trajectories we have seen that to optimise cotton supply, sometimes companies won’t need to focus on providing inputs for cotton, but for other crops instead. Because farmers have a multi-crop reality, decisions, opportunities and solutions are also often multi-crop.

User centered systems

Starting from the two examples mentioned, we believe that the design of a Management Information System should not focus on creating a system that works just for one value chain and one buyer. A Management Information System should facilitate the exchange of relevant data and analysis best by enabling and motivating producers and producer organisations first and foremost to run their own business. If they do so in a professional way the internal data system of a producer organisation will be able to provide the relevant data to buyers without extra work, saving costs and efforts on both sides. In other words, when the user and the user reality is central in the design of a Management Information System, we believe the same goal can be achieved in a more efficient and effective way.

Recently, during a role-playing game centring around the process of setting up a Management Information System, all actors were really busy with the MIS as such, its technological possibilities and the ideal situation. Then the person representing the farmers said: “You can talk a lot, but if my perspective is not taken seriously, I am out. And if I am out, you can stop talking.” And with the serious professionalisation of many producer organisations that we currently observe, this is something that can happen in real life as well.

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