Organisations that have been through cycles of supply chain changes, spend analytics, consolidation and segmentation in procurement count on predictive analytics to forecast revenue, identify opportunities in the market, mitigate disruption and do much more. Such prediction stems from advanced statistical and modelling attributes and helps understand commercial and technical attributes. The real-time availability of data and data visibility, collection of third-party datasets through advanced warehouses can help deliver efficient supply chain outcomes that are otherwise difficult for the procurement leaders to achieve.
Prediction in procurement also requires higher levels of analytical modelling capability in order to harness the power of multiple computing systems so that data can be pulled from systems, machines and social media in the real-time. It needs further study as it is seen to be an important process in the procurement function.
In designing predictive systems, it is essential to pay attention to which kind of data is important and what kind of data has been cleaned. Analytical talent is required to pull right kinds of data from different pools of data in order to integrate data into object-oriented database.
This indicates that it is necessary to engage the right people in data modelling processes that helps predictive analytics. There is a need for subject matter experts more than data scientists who understand the dynamics of systems, data structures, modelling approaches including simulation, clustering techniques, sampling technologies and statistical testing and engage with the organisation in a consultative manner. These kinds of analysts can prove immensely beneficial for an organisation but are usually difficult to find.
A stronghold basis in analytical systems can only be achieved through investments in procurement processes such as contract management, spend analytics and transaction procurement systems. In the larger scheme of things, it is paramount for procurement to comprehend the issues of stakeholders and then be able to articulate questions that needs effective accountability.
Can supply analytics be generated sans data on contract, spend and supplier life cycle? Many answer in the affirmative. When asked if it was plausibly more difficult to generate analytics without contract visibility and spends data, many still answer in the affirmative indicating that it is essential for procurement to make the optimum use of whatever data is available.
Procurement leaders also point out to challenges that pervade organisations looking for trustworthy and reliable analytics for stakeholders due to lack of systems. As part of the research, it was found that only some rare organisations that were able to derive high level of spend data integrity across organisation units. Import of third-party external datasets in order to fill the gap in the availability of internal data can be an advantage if creative thinking is used to exploit it. In order to achieve excellence and an edge, procurement can derive insight through analytics and making use of the best cognitive technologies while unravelling all types of data that has been kept hidden until it transforms the procurement landscape to a great deal.
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