The role of Procurement is changing. Okay, we know – you’ve heard that before. But after the events of 2020 and their ongoing repercussions, that change has been hugely accelerated.
Increased market volatility and a high risk of supply chain disruption have placed pressure on Procurement teams to maintain profitability, better manage working capital, mitigate third-party supplier risks and drive business sustainability. As a result, those teams are playing a more central and strategic role in their organisations.
This role requires the latest tools, technologies and insights to succeed. And at the forefront of those technologies is Procurement Analytics.
The webinar covered how Procurement has evolved as a function, how analytics can provide value, the factors that will be critical to your success, and more. Here’s an overview of what we learned.
The changing role of Procurement
It’s hard to find many positives in a global pandemic. But for Procurement teams, the last year’s events have seen the function elevated to a new standing in many organisations.
Departments are now expected to drive value beyond savings. They are responsible for effectively managing category and supplier risk, guiding supplier-enabled innovation, ensuring organisational agility, and steering digital adoption and sustainability initiatives.
Feedback from those that attended our webinar echoed these sentiments. When asked for the top three impacts on their business environment, we saw a relatively even spread across a range of drivers:
- Budget pressure to recover profitability and preserve cash – 64%
- Higher risks of supply chain disruption – 55%
- Changing ways of working – 52%
- Increased market volatility and complexity – 51%
- Drive for sustainability – 43%
- Skills evolution – 32%
At the heart of each of these demands, whether it’s reducing risk or improving profits, is the need for insight-led Procurement. And that’s where Procurement Analytics comes in.
What is Procurement Analytics?
Simply put, Procurement Analytics is the process of turning data into actionable insights to address Procurement priorities.
At its most basic level, Procurement Analytics can help us make data-driven decisions to better manage spend and supply chain risks among other things. But there’s a great deal more to it than that. There are four stages of Procurement Analytics maturity that make up a roadmap for change, from the basic use of data to more advanced modelling and insight.
- Data management
The first step of a procurement analytics journey is to build a robust and standardised repository of data that can provide insight into your organisation’s purchasing.
- Descriptive analytics
Descriptive analytics can then help you understand the story that data tells and provide insight into real-time reporting metrics and KPIs. This will help you to control spend and identify where it’s happening.
- Diagnostic analytics
Using external and internal benchmarks, category levers, and risk and root-cause analysis, you can then begin to understand precisely why these things are happening.
- Prescriptive and predictive analytics
Finally, using predictive and prescriptive analytics alongside forecasting and simulation models, you can gain insight into what will happen next – and optimise strategies to get ahead of the game.
Using analytics, Procurement functions can help develop, implement and manage new and more effective category management processes. The result can be huge savings, reduced risk and greater organisational efficiency.
But doing this on any level requires investment – not just financially, but in a technological and strategic sense, too.
Roadblocks, key considerations and readiness
Of those that attended our webinar, only 9% said they’re currently implementing predictive and prescriptive analytics. And 29% said they were still largely focused on spend analytics.
So, what’s slowing adoption? Most organisations are aware of the value of analytics – more on that later – but they often struggle with data-, insight- and adoption-related challenges.
There are four common obstacles here:
Lack of quality data
Any analytics solution is only as good as the data that fuels it. But many organisations struggle to access clean and reliable data from the numerous systems across their IT landscape. In fact, 82% of our webinar attendees cited data-related issues as a barrier to analytics success.
Obsolete tech, including the multiple, home-grown custom ERP systems that many Procurement organisations rely on, can also prove a substantial barrier to actionable insight. Even today, many Procurement functions rely heavily on spreadsheets, which makes extracting data a mammoth challenge.
For analytics projects to work, you need the proper support and funding. But convincing stakeholders and proving ROI can be difficult. That said, there’s perhaps never been a better time to put a business case together than right now.
A shortage of talent
Finally, driving effective analytics requires relevant skills. But a shortage of talent can make those skills hard to come by.
Are you ready for Procurement Analytics?
With these factors in mind, it’s essential to assess your readiness before embarking on any procurement analytics projects, both from a technical standpoint and a business one.
You need to evaluate the current level of technology adoption in your organisation, and whether your team is tech-savvy enough to adapt to new technologies quickly. And you need to ask if you have the right skills in-house to realise your analytics strategy.
From a business perspective, you also need to consider whether or not you have the stakeholder buy-in and company culture required to adapt to change and relinquish outdated practices and technologies.
Finally, you need to have the right policies and processes in place to support the adoption of your analytics strategy, including a clearly defined framework of roles and responsibilities.
A multimillion-dollar opportunity
The good news is, if you possess the required framework for Procurement Analytics, the benefits are undeniable. And there are numerous real-world examples to illustrate that.
During our webinar, Omer highlighted how one global distribution company saved over $350 million across three global categories. He also shared how a leading steel manufacturer reduced spend by 10%, and how a consumer goods company made $20 million in savings through dedicated commodity forecasting.
You can learn more about each of these projects, and get a 10-point checklist to ensure success in your own analytics journey, by watching the webinar on-demand, here.