Category managers face a deluge of data from internal and external sources – but this data is only useful if it delivers insights that enable more effective decisions.
Many companies have yet to overcome the problems of poor quality data, held on disjointed legacy systems. Historical spend data is often uncategorised and needs significant cleansing before it can form the basis of a forward-facing outlook.
The fast-developing disciplines of advanced analytics and data science can be readily applied to procurement processes including commodity forecasting, spend visibility, and supply and demand planning – but these new tools will only be relevant if the base data is accurate.
While there are now many external sources of market and commodity information, they’re often based on a variety of data collection methodologies and can provide conflicting insights. Meanwhile, the explosive growth of social media and proliferation of information available from online sources adds to the external noise and clutter.
Overcoming the data deluge
In the digital age, procurement teams can access an immense amount of information and new data streams are emerging every day. Identifying those that are most valuable and relevant presents an immense challenge, and the availability of actionable insights remains limited.
It’s vital to avoid becoming overwhelmed by multiple internal and external data sources, the disparity of information from different sources, and the skills gaps you might face in handling and manipulating data.
Key considerations for CPOs
- Start by defining the business problems you need to solve, the decisions you need to make and the answers you want to get. Once this is clear, you need to assess the data sources which will help you achieve these objectives, and the most efficient way to get the insights you need. It’s easy to get bogged down by data, so it is important to stay focused on your objectives.
- Be open to adopting a flexible approach to data access, standardisation and analytics based on the type and quality of your base data. For instance, automated extraction might not be possible for some datasets, so you should consider manual interventions rather than an expensive, long-term project to change or make improvements to the base data source.
- Take a phased approach to data and analytics, focusing on small incremental steps rather than big leaps. For instance, diagnostic spend reporting based on the correct categorisation is a precursor to more advanced predictive spend forecasting. Many organisations struggle when they try to apply predictive analytics and advanced tools without improving their data quality. In these cases, the correct approach is a combination of human intelligence and technology, rather an outright reliance on automation.
- Consider creative ways of solving your procurement issues and achieving targets by harnessing the power of data analytics. Advances in analytics methodologies and technology now enable analysis of unstructured data in invoices, POs, contract management systems and more. Stay abreast of latest developments across your sector. Applying a ‘test and learn’ methodology can accelerate innovation, help demonstrate the value of new approaches and provide the evidence to support a business case for wider deployment.
As of today, very few procurement organisations are using data optimally to drive more effective decision making.
Advanced analytics help consolidate data and draw meaningful inferences – it tells you not simply how things look today but how they will look and perform tomorrow. It should be your goal to embed deeper analytics into your day to day functioning to seek better spend visibility, predict outcomes better, supercharge category leadership with the right data sets, dashboards, forecasts, and models.
While today’s data deluge poses problems, it also presents a rewarding opportunity for procurement professionals if managed in the right way.