How to Get Your Procurement Data in Order So You Can Survive in a Digitalized World

Procurement as a function has evolved significantly over the past decades moving from a transactional function centered around P2P (Procure to Pay) activities to a strategic business partner helping companies worldwide leverage the value of their supply base whilst minimizing risks to their operations. This shift has been a key part of our functions story until now but looking forwards the shift to digitalization will redefine the function once again.

Tech based solutions such as Artificial Intelligence, Machine Learning and the Blockchain have been touted as game changers in years to come. Well the time has come; the game is changing across our function. Technology is changing the way we do business and from here on it will only become an ever more valuable part of our daily lives.

But I’m sure your reading this and thinking “sure, but I don’t see how that’s going to happen in my business”. That is the key challenge for most Procurement organizations, how to start on a digital transformation.

Regardless of the solution you are implementing be it AI, Machine Learning or Blockchain there is one crucial backbone, data. Clean, accurate and consistent data is crucial for any digitalization journey. The difficulty is this is the least digital element of digitalization, 80% of what is needed at this stage must be done by humans.

Take for example the common Procurement issue of mis-classification of suppliers, if you teach a system than supplier X provides HR services and has done all year how is the system to know that actually they are an IT firm? Furthermore, data cleansing can be a major issue. Strategic procurement teams are often the receivers of information not the makers, as a result there’s often a need to cobble together data from multiple sources. If everyone is left to their own devices to combine this data, you’ll end up with one hundred people doing it one hundred separate ways.

To overcome this here are 5 steps for getting your data in order.

1. Get yourself a data expert

To bring together all the different data sources and cleanse them so that they can be used across the function every Data Governance is key. Every Procurement function should have a central Data Governance team who are responsible for gathering, cleansing, and distributing all the data the team needs. It should be this team and this team alone that determine the data validation rules for the function as a whole, manage supplier classification and build connections through a data warehouse to give category managers data at their fingertips.

2. Invest time and effort in your supplier classification

For Procurement functions spend taxonomy is the holy bible that governs so many of our subsequent workstreams and processes. Getting it in shape is crucial. The problem with most is that they are designed in a way to fit a round peg into a square org chart shaped hole. Services that don’t fall neatly into the design of the Procurement organization are often swept under the rug or classified in a way that forces them to fit leaving them incorrectly classified and unaddressed for the rest of their days. For this same reason it is also best to avoid any “other” options in your taxonomy. This is a get out of jail free card for anyone that doesn’t want to invest the time and effort to categorize correctly.

Instead build a taxonomy that is dynamic and well defined. An effective taxonomy will need at least 4 levels to reach the level of detail with which most suppliers identify themselves. Each of those sub-categories should have their own definition. If a supplier doesn’t fit that definition, then a new sub-category is needed.

3. Bridge the gap between the money and the product

Too often Procurement functions only talk hard currency in the form of spend without having an effective way of knowing the product and most importantly the quantities. It’s like going to your supermarket and buying one apple for 50p over 3 for £1 and thinking you got a great deal. Yes, it is cheaper, but if you need more than 1 you’ve made the wrong choice.

By incorporating spend data with other data streams you can begin to get instance access to volume based spend data. Services often harder to capture vs direct materials but can still be achieved by mandating data collection in key stages of the Procurement process.

4. Make data capture critical

Whilst cleansing and organizing data is without a doubt the hardest and most work intensive part of the digitalization journey capturing future data is just as vital. Every piece of data is valuable and should be treated as such.

The best place to start here is by setting and following your own data governance standards. Often that will mean mandating templates for data capture from suppliers, utilizing central data management systems and working with your data team to ensure that every new piece of sourcing, every interaction with your stakeholder and every invoice is scraped and stored for the future.

Here there are tools to help character reignition tools can be leveraged to scrape paper documents to turn your information digital. Chatbots too can be used as a useful tool, not only do they provide an efficient way of communicating they also capture data like no conversation ever could.

5. Make that data tell a story that matters

Last but by no means least, you must find a way to make that data mean something. As more companies invest in innovative technologies the return on investment will be scrutinized and challenged like never before.

To make your digitalization journey a success use it to drive improved savings calculations that allow you to demonstrate real EBITA improvement. By having improved data, you start to really show how procurement events deliver a real step change in costs over time.

Data is the future of not just Procurement but business. There is no better time than now to begin your digitalization journey, tomorrow will be too late.

Note: All advise, comments and opinions are my own and not reflections of past, present, or previous employers.

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