Procurement Strategy for an Unpredictable World

The future of procurement strategy is data driven. In fact, it should already be a reality in your organisation. I don’t believe this is something I have to convince you of. We all accept it. My question is: are we actually using data correctly? Do we really understand what data is? Do we even know if we have access to all the relevant information?

The vast majority of organisations are missing key elements in their data. Not enough attention is paid to contextual information related to purchase decisions, and we aren’t taking advantage of the vast wealth of data available externally.

The Perfect Marriage of External & Internal Data

Internal data

We have many streams of internal data to feed into our procurement strategy. ERP and general ledger information, purchase orders, data from suppliers, even Excel and Sharepoint files. The problem is that this data isn’t collated in a way that’s useful to procurement; it’s typically optimised for the finance team. Considering many organisations base their purchasing decisions entirely on internal data, key information is often invisible.

Data analytics in 2021 can change how we deal with this. A few years ago data analytics providers might have presented the data nicely and made it easy to view, but it wouldn’t have offered much in the way of actionable insights. Now, however, the more sophisticated analysis services can help uncover important factors like purchase order compliance: how many goods and services purchased are done so with a PO? What spend is on contract or – even better – what is the correlation between spend off PO and overall departmental compliance?

This today is the base level of what we can achieve; once we have worked through the more complicated compliance issues and tied together internal data sets, it’s time to look at how we can build in external data in order to make the data richer and help procurement departments derive truly actionable insights.

External data

When we think about where we’re buying our goods and services from, it’s important to think about political and environmental factors in those markets. In an unpredictable world, this is the key to making it as predictable as possible. Again, data analytics and AI is your friend.

Scenario. Your business requires textiles, which you import. You adopt AI that continuously scans news sites for sentiment and for the words [the country you import from], [union], [disruption] and [textiles]. It soon starts flagging articles mentioning threats of union strikes at ports in the coming weeks. In response to this, you switch to suppliers in another country. A few weeks later, your original supplier is strangled by union strikes at the ports they use.

This is not the future. AI is being used exactly for this purpose today, helping organisations avoid political upheavals and reduce supplier risk.

Now let’s take a look at an example of what can happen when you combine internal and external data.

In 2011, Toyota’s supply of computer chips was severely compromised when a tsunami hit the shores of Japan and wreaked untold damage. Its main plant was knocked offline for three months. In response, Toyota went to work, scouring its supply lines to find its most vulnerable spots in the hope of nullifying (as much as possible) future environmental events. One of the contingencies they put in place was a 6-month stockpile of computer chips that would help them weather a similar storm.

Welcome to 2020 and COVID-19. A chip shortage is crippling the auto industry as the pandemic shuts down manufacturers across the globe. Toyota, however, has a six-month buffer on its competition. For them, it’s a game changer.

How well do you know what you’re buying? Data isn’t just spend analysis!

One of the most important aspects of sound procurement is knowing the right questions to ask. This can only be done if you have an intimate knowledge of the product you are buying. One hugely important piece of supplier data is the bill of materials (BOM) (which many purchasing organisations don’t pay enough attention to).

If you know the parts that go into an item you’re looking to buy, you can have the manufacturer break down the cost of each component. You can then benchmark these prices against the competition. If other suppliers are manufacturing particular components at a cheaper rate, this is something you can negotiate on. It may be that there’s a perfectly good reason why the original manufacturer spends more on that component (perhaps they make it to a higher standard), but you won’t know if you don’t ask. In negotiation, knowledge is power.

This type of data can be crucial in maintaining (and reducing) your cost base. Also, this level of sophistication can yield savings and help you manage your risk profile. Organisations that focus on building and managing this type of data capability will also then have the ability to tie it in with other data sources for increased richness.

This is procurement strategy for big and small

Utilising multiple internal and external data sources is not solely for Toyota or the Fortune 500s. There is absolutely no reason why SMEs can’t take advantage of modern AI and machine learning to reduce supplier risk, increase the ability to drive savings as well as mitigate, as far as possible, environmental and political factors.

It’s time to get control of the data you currently have and supplement it with relevant political and environmental information. Purchasing Index can guide you through the implementation of the latest data analytics and help tailor it to your organisation. The goal is to make this information readily available and understandable to anyone in the organisation involved in procurement strategy.

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