Insights & Ideas

Five Tips to Implementing Self Service Spend Analytics

From algorithms to Answers

Collecting and analyzing data is important to the success of every endeavor. For years, third-party spend data has been collected and interpreted using spreadsheets, much to the incredulity of other, more advanced, technological solutions. However, the explosion of big data has made this approach redundant – in theory, at least.

The increasing volume, velocity and variety of data requires intelligent tools that can gather and integrate data from multiple sources, cleanse and enhance it and enable users to visualize it – all while being intuitive for use, so that users can become closer to their data.

In practice, organizations are still working to understand what the potential of this data means to their business, and how they can build it in to their functional capabilities. 

Why current thinking is holding organizations back…

The limitations of spreadsheets for spend analysis restrict the appeal of long-standing methods, methods that yet remain synonymous with purchasing and finance processes. In the past, procurement has used spreadsheets to identify savings opportunities. However, what’s lost through these more basic, linear, techniques is more than just efficiency – information that drives sourcing, spend and operational decisions isn’t captured in the traditional tools used by procurement.

For example, globalization has produced integrated supply chains that make managing risks more difficult than before. Tools are needed that enable cross-functional and geographically dispersed teams to effectively manage and mitigate supply risk. Elsewhere, there’s pressure to know your suppliers, their performance, compliance matters, and to better understand your stakeholders and their spend habits – the realization of recent years is that all these levers rely on having visibility and control. That should be a catalyst for change.

…And why a spend analytics revolution is at hand

As big data and globalization evolve, so too the market for spend analytics has evolved. Greater automation has improved efficiency so that more data can be more accurately processed and accessed by business users faster. Crucially, self-service cloud-based solutions have emerged that enable lots of people to access the data at a time and place that suits them, and crucially, be able to collaborate on the same data sets from remote locations. And these people are looking for different things so the ability to manipulate and update the data becomes critical.

The business case then becomes a question of demonstrating immediate value to the business, with a convincing case for ease of adoption and, ultimately, better governance already in your hand. This isn’t just a case of tapping into cost savings: it’s enabling spend management right across the organization.

This transformation serves as something of a virtuous cycle: The more procurement can drive decision-making and evidence the value that comes from spend data, the more it can leverage it to positively impact the competitiveness of the business.

Top tips to implmeneting spend analytics 

  • Maturity - The maturity of procurement in the organization and the market sector may influence the type of spend analytics solution required: immature organization and/or highly regulated market sectors like finance, pharmaceuticals and defence may need more support to deliver the full benefit.
  • Planning - Agree the roll-out strategy in advance. This should include an internal communications plan, access rights and support from the provider.
  • Highlighting Benefits - Target categories of spend to “showcase” the capability of the tool. This may include categories of spend that are traditionally difficult to analyse because of the high wide variety or geographical spread of products such as MRO and telecoms or that are difficult in impose controls such as cleaning and waste removal.
  • Future of Procurement - Consider how procurement’s role may change as users will become actively involved in saving opportunity identification, supply risk management and innovation.  Buy for today, but plan for the future is important so whatever tool you choose, ensure that it can meet your data analytics needs tomorrow.
  • Review - Review usage regularly and provide on-going support to new and existing users.  There is no point investing in a technology if it’s not going to be used.  It’ll come back and haunt you.

Conclusion

Globalization and big data have led to a paradigm shift in spend analytics. It is no longer a static, manual process run by procurement in isolation to identify savings opportunities. Increasingly complex supply chains and a wealth of data have given rise to sophisticated tools that are available to a new audience.

The providers of these self-service tools have approached the market in different ways. There is a compelling case, however, to say that the ones that offer highly automated and intuitive solutions will succeed as the emphasis moves from identifying savings opportunities to more value-oriented activities such as risk management and capturing innovation.

The future of the function depends on the ability to capture and leverage spend data – making the case for that technology and recognising what solution can be best deployed to meet the needs of the business should be top of any procurement team’s list.

 

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