Big Data is revolutionising business processes. With this newfound ability to reveal patterns, trends and associations at deeper levels than ever before, organisations have the potential to solve almost any business problem.
Gaining access to vast volumes of data and the ensuing insights is so beneficial, in fact, that businesses have made huge investments into data acquisition and analytics programmes. While many have only seen relatively modest cost improvements, it’s important to note that Big Data analysis helps to develop more personalised customer relations and enable greater efficiencies across the board.
>See also: Where does a business’s data live?
What’s more, companies are using analytics in programmes that increasingly involve chief procurement officers (CPOs), who now have a far stronger voice in the c-suite. Procurement departments are even using big data to optimise budget allocation for marketing and localisation strategies. Applying big data analysis to procurement and marketing relationships can significantly improve each team’s performance, especially in determining the ROI of every investment.
From a procurement perspective, specifically, big data goes a long way in two key areas of sourcing: spend analysis and automation.
Spend analysis is perhaps the most obvious application of Big Data in procurement. Identifying spending patterns can provide CPOs with ways to reduce costs, mitigate supply chain risks, improve business processes, and manage supplier performance, to name but a few.
Lionbridge’s 2017 ProcureCon report found that 59% of CPOs are investing in spend analytics software to provide ROI clarity, and the reasoning behind this is clear. Procurement’s ability to use data to demonstrate value to business stakeholders is the department’s strongest asset for maintaining its strategic influence on bottom-line impact: for example, validating the value of localisation.
A grey area for many, the ability to measure return on localisation investment is vital both for organisations that already work with language service providers, and those considering the initiative.
Localisation may be complex and unique to every business, but adapting content to specific markets while measuring performance is a valuable business process for enterprises looking to deliver globally optimised products. Using big data, determining the worth of localisation is no longer a guessing game for procurement; it’s a formulaic approach. It would be no surprise, then, to see even more businesses invest in this area.
Automation is key
Even so, while the benefits to be gained from big data analysis are clear, the process of sourcing this data is seen as a mammoth task – one that may be deterring businesses from investing in analytics.
Automation is the buzzword here. The ProcureCon report found that automation technologies, as well as third-party automation service providers, are two key resources allowing CPOs to collect data in faster and easier ways.
Of course, automation provides many other benefits in terms of operational efficiencies, but its ability to speed up big data analysis has liberated the CPO. In turn, locating and analysing the right data is empowering companies to deliver results optimised for ROI.
Solutions are now advanced enough to consolidate the spend data of an entire global enterprise. Organisations investing in these technologies no longer exhaust their efforts on data collection – instead, they free up valuable time that can be spent putting the insights to good use. As a result, the conclusions drawn from this analysis are more likely to drive true innovation and change.
If the correct investments are made, data analytics can provide CPOs with insights that will shape their company’s future. Procurement strategies – including tackling complex spend categories like localisation – can now be assessed with greater clarity, and that’s all thanks to data and automation.
With fully-automated, analytics-driven, and client-friendly sourcing tools, CPOs are able to locate greater amounts of relevant data with ease. Businesses must now scale up their investments into data analytics to reap the benefits.
Sourced by Lionbridge