Turn data into insight
Continuous flow of information provides more and more data to be stored but are we actually utilizing the existing data, that we have, as much as we could? Are we able to make decisions and predict future quickly enough based on the available data? As Carly Fiorina, former CEO and chair of Hewlett-Packard Company, once said: “The goal is to turn data into information, and information into insight.”
Data has been on most of our lips for quite a few years. Big Data, Artificial Intelligence, Augmented Reality have been trending in technology field, but majority of organisations are just starting to tip their toes on analysing data pools. But do organisations have their basis covered with collected sets of data that is the foundation of all data-based solutions?
It’s often forgotten how important for an organization it is to provide helpful information that can guide future decisions or capture potential process or activity bottlenecks. Seldom the system landscape is homogenous, which means that it’s important to be able to obtain the system’s info to a place, where it can be viewed or even enriched with other system’s data to provide more comprehensive view.
Way too often, data is only looked through reports containing data from an individual system like CRM or ERP, which may not represent the whole process end to end, even though data coming from those systems may be essential part of the total view. For example, when data is available in real-time and a global pandemic hits your business, it can be useful to obtain the information in an ad hoc manner, to be able to react immediately.
Many organisations have turned their focus on a specific end-to-end process rather than only on one system. It is essential to provide process transparency so that pitfalls can be avoided, and process enhancements can be implemented to obtain savings and further efficiency. This is what provides real benefits and additional value to the whole organisation and push the business into gaining even better results.
Good example of process data is e.g., the ratio between strategic and other partners, which the organisation has frame agreements with. Do you know if you are actively cooperating with all vendors that you purchase over a certain amount in a year, quarter, or month? Is the typical turnaround time from starting a sourcing event to closing contract negotiation a known fact? Can you plan the workload of experts that execute the procurement events, so that there is right number of events open, which can be efficiently handled without overtime or overloading the experts? All these answers can be provided with available data.
The big step is to look at your entire process critically and ensure you can utilise and potentially enrich different vendors’ systems data as you need. This is the first step towards being able to focus on e.g., AI related workflows in the future and gaining the most benefits of future technology steps.
If you have the data, use it!
Read also how procurement analytics can convert your bad apples into KPIs and download our article on how AI and other emerging technologies affect knowledge management in procurement.