What can procurement learn from Big Data thinking?

What can procurement learn from Big Data thinking?

November 28, 2014

‘Big Data’ is rapidly becoming an integral part of the management information landscape. As such, it’s equally clear that it will play an important role in helping procurement professionals make good decisions in the future. In this article we investigate what procurement teams can learn from Big Data thinking, review its advantages and suggest some initial approaches to using Big Data in your organisation.

‘Big Data’ is rapidly becoming an integral part of the management information landscape. As such, it’s equally clear that it will play an important role in helping procurement professionals make good decisions in the future. In this article we investigate what procurement teams can learn from Big Data thinking, review its advantages and suggest some initial approaches to using Big Data in your organisation.

What is Big Data thinking?

Big Data is most usually defined as ‘the analysis and use of information of extreme size, diversity and complexity’. It has emerged simply because our capacity to generate and store data had doubled every three years since the 1980s. As a result, by 2020 analysts estimate that we’ll have 300 times more data available to us than we do today. The question is how can your organisation make use of it?

Big Data thinking means seeing beyond the performance of individual tenders and starting to see trends across all of your procurement activity

A further characteristic of Big Data is that it’s also often so unwieldy and complicated that conventional legacy data-processing applications will struggle to handle it effectively. But don’t be put off. Procurement is ideal territory for yielding strong benefits from Big Data thinking. Procurement produces massive amounts of data, which is often widely dispersed across different systems, operations and geographies.

Finally, in our view, Big Data thinking in procurement begins with seeing beyond the performance of individual tenders and starting to identify trends and patterns across all of your procurement activity. In due course this will likely involve integrating internal data, such as spend and contract data, CRM systems, and warehouse management data, with external sources such as market, transportation and regulatory data, financial ratings, supplier financial data, and supplier databases, and analysing the results. It seems like a big challenge – and it is – but there is a great deal to be gained. The most important step, though, is to start on the journey.

What are the benefits of combining Big Data and procurement?

Broadly, the benefits of Big Data thinking will be transparency, insight and actionable information. Of course ‘information out’ can only ever be as good as ‘information in’. That said, proponents of Big Data expect it to produce, among other things:

  • a better understanding of participants in the procurement process and their behaviour
  • shorter procurement cycle times
  • the ability to identify market changes earlier
  • optimised operations and inventory
  • new revenue opportunities
  • mitigated supplier risk, e.g. to spot over-exposure to a financially fragile supplier
  • leverage in supplier negotiations
  • data that will help develop Supplier Information Management, rationalise the supplier base, and develop suppliers and supplier relationships.

How to approach Big Data in Procurement

A recent Accenture study of more than 1,000 senior executives found that while most organisations have high expectations of Big Data in procurement, in reality many had difficulty adopting it.
This is because the challenges of Big Data include analysis, capture, curation, search, sharing, storage and transfer. Taming all this complexity relies on effective management of the five key attributes of Big Data:

  • Volume and Variety apply to data collection, and whether your platform allows for the capture and analysis of procurement activity from across the business – at a granular level. You also need the capacity to integrate all your data in a meaningful way, from across multiple systems.
  • Velocity concerns the ability to deal with the speed at which data is created, as well as how soon output information becomes available. Real or near real-time information delivery is one of the keys to meaningful Big Data analysis. Organisations with high purchasing volumes will likely find that the manual analysis of procurement data is no longer practical.
  • Visualisation is about how data is sliced, diced and presented – enabling you to spot patterns and changes visually. Most procurement teams won’t have the time to do this effectively without having the tools that let you construct visual representations – like dashboards and scorecards – from which crucial insights can be gleaned easily and quickly.
  • Variance is seeing deviations from the norm. This is extremely important if practitioners are to take meaning from lots of Big Data. Benchmarking and pattern spotting is key to taking action – which is, after all, the most important aspect of doing Big Data. Improving what you do already and reacting to change and opportunity is the ultimate aim.

Moreover, to start on Big Data organisations need a procurement platform which processes data itself, rather than one which is only capable of handling documents. This calls for a data-centric procurement system of the kind supplied by Nextenders. Data-centricity means you can make use of all the information in the system – you can select, analyse, import, aggregate, manipulate and process it. Without data-centricity, Big Data can’t start. Essential too are well-designed databases, and people with deep analytic skills, as well as a thorough business and industry knowledge.

How to start combining Big Data and procurement

Success from Big Data relies on clear, early thinking about what you measure and what you do with the results. What you measure should be guided by your organization’s overarching mission and vision. Are you about customer service – then that’s an area to focus on. Are you about excellent quality – then think about the critical path to achieving quality and go there.
We suggest you begin by acquiring some basic metrics.

  • Benchmark key parameters such as pricing, unit costs, number of bids, etc. Look for patterns and deviations from the norm that ‘red flag’ areas for improvement or action.
  • Look at capacity: how many tenders are you starting and completing per month/quarter? What is the throughput and average cycle time for your procurement? This can highlight areas where procurement is and isn’t working well.
  • Look at price optimisation in repeat procurements. If prices vary for the same goods and services, ask why.

Information that’s not acted upon is as much use as none at all. Real benefits come when insights change behaviours

As to what you do with the results – never forget that information that’s not acted upon is as much use as none at all. A key to achieving real benefits with the results is ensuring that behaviours change as a consequence, and this calls for genuine engagement with people across the business to ensure that change is embedded.

Conclusions

Big Data is set to be an important discipline for high performing procurement operations in the future. It will likely be a critical business capability and a key determinant of future success. McKinsey has already called it ‘the next frontier for innovation’.

Moreover the momentum of adoption is gathering pace. In 2013 Gartner found that 42% of respondents to its latest worldwide survey had invested in Big Data or were planning to do so within a year , seven months later the Wall Street Journal reported that nearly two-thirds of businesses had already invested in Big Data technology or planned to. Systems that can effectively collect and analyse all kinds of procurement data across a global organisation are fast becoming a core area for technology investment.

Implicit in this is that those who do Big Data early and well will have a competitive advantage over those who don’t. Conversely, the biggest concern around Big Data might well be the failure to engage. The danger is that those who fail to adopt will get left behind.