A recent Information Age article has highlighted the effect that software developments and new algorithms can have on business decision making – and therefore their performance.
According to the article’s author, managers make decisions based as much as on assumptions and hunches as they do on evidence. And the odds are that the information they do use hasn’t been analysed fully or objectively. The obvious conclusion is that managers are prone to making the wrong decisions.
Because technology takes account of all of the factors and weighs them appropriately, it is a better predictor. However, the article emphasises that the more big data is used, the more need there is for human review and collaboration. This is because managers must constantly question the assumptions and factors upon which the automated analysis is based to ensure that the outcomes are right for their organisations.
This means that business information systems must be predictive rather than descriptive. In other words, the models must be able to tell managers what to do, not just produce volumes of metrics and indicators. Large organisations are beginning to use these analytics alongside balanced scorecards to make strategic decisions and manage overall performance.
What’s interesting about these developments is that managers needn’t worry about losing control. The article argues that increased automation will ensure that management teams work more collaboratively to ensure that the system recommendations are implemented properly and behavioural bias is removed.
At the moment, the kind of operation described above generally requires the use of trained statisticians but developers are working on packaged software models. This may give smaller businesses access to significantly improved and sophisticated information management systems in the future.
Read the full article here: The new scientific principles of management.