Work smarter, not harder:  5 Great Examples of Smart Procurement

New technologies such as artificial intelligence, visualization and advanced analytics offer great promise – but only if the underlying data is of top quality, writes Malcolm Wheatley

Smart Procurement is a catch-all term for AI (including sub-categories such as machine learning, natural language processing…), RPA, advanced analytics, visualisation and more.  In a world of catchphrases, it goes beyond just a marketing term, as this is happening in your organisation. Or it soon will be. Smart Procurement is moving beyond areas such as spend analytics, to actually taking action and delivering efficiencies.  Far from making the role of Procurement obsolete, these technologies will project Procurement into a whole new era of growth and added value by freeing capacity and enabling more strategic decision-making.

In a recent report by Procurement Leaders: Smart Procurement Insight, in association with Ivalua, several examples of this Brave New World are highlighted, and shine a light for Procurement Professionals on the road to Smart Procurement.

Here are 5 user cases which demonstrate the versatility and usefulness of Smart Procurement technology:

1.Procurement Digital Assistants

Dealing with thousands of routine questions – UCB has developed, in-house, an AI Chatbot, called Aria and in doing so they are experiencing a superior user experience, higher productivity and greater compliance.  Digital Assistants, such as UCB’s Aria do not mind how many times you ask them whether an invoice has been paid or how much remains on a purchase order. Much of the daily grind of Procurement employees is spent dealing with these GroundHog day type enquiries and this technology will free your employees from this drain on your resources. Such technologies are starting to be embedded in software provider suites, which offers even more accessibility and better results, particularly when such suites are built on a unified data model.

2. Procurement Chatbots

Pedro Barata, Digital Supply Chain Lead at Vodafone Group estimates that using cognitive or Smart Procurement systems to support the finding and buying of goods and services from an external source, will free up Procurement at Vodafone to focus 90% of their time on Strategic Sourcing and partnering.  Vodafone have developed 2 Chatbots, one called Tobi. Tobi is programmed to guide local users in Vodafone’s global operations to the correct category managers and buyers.  A second chatbot helps users purchase non-standard items.

3. Spend Analysis Powered by AI

“AI has had several false starts but this time it’s different,” says Bill McBeath, chief research officer at supply chain analyst firm ChainLink Research. “The momentum behind AI looks unstoppable: its time has come.”  One of the earliest applications of AI for Procurement was in Spend Classification. Early results offered marginal improvements and had the unintended side effect of making classifications a “black box,” a real challenge in cases of misclassification. Yet recent advances are greatly increasing the value, particularly when implemented so as to maintain visibility into the logic behind specific classifications. AI systems which know who the supplier is and where in the organisation the services or goods are being ordered and used, can help by speeding up classification into spend hierarchies and applying correct codes, saving significant time and improving analysis.  Invoices and POs often have limited information and if organisations can cut down the time a human needs to spend in any part of this process, that can’t be bad.

4. Smart Procurement for Sourcing

Fannie Mae, ranked the world’s fifth-largest financial services company by revenue in the Fortune Global 500, have taken this further by creating category-specific spend dashboards by pulling together data from multiple systems to provide insights that help identify new savings opportunities.  Sylvie Noël, CPO, of French Insurance giant Covéa, is also enthusiastic about the impact of Smart Procurement. “Preparing a contract summary can take 10-20 minutes, sometimes longer,” she says. “Sourcing and answering users’ queries takes time, with a lot of documents to be handled. Yet preparing documents and filing information or manually preparing contract summaries doesn’t add much value: my buyers have got better things to do with their time.”  For this reason the organisation which she runs is trialling projects in cognitive sourcing, where chatbots and smart AI-driven contract summaries automatically extract the relevant data and terms from contracts and present them in a summary sheet for review or signoff.

5. Invoice Data Capture with AI

You will read in the report that UCB, actually developed their AI solution in-house as there was no technology vendor ready at the time.  Ivalua is one of the organisations at the forefront of leveraging AI to automate Invoice Data Capture, embedding this capability in its suite. If you are interested in the technical details about this you can read the recent blog by Christopher Bourez, AI Architect at Ivalua – Invoice Data Capture with AI: Rule-Based versus Cognitive Field Extraction.

Getting Started with Smart Procurement

If you are not among these early adopters, don’t panic.  They are ahead of the game and we can all learn a lot from their experiences and by speaking to providers like Ivalua and experts like The Hackett Group, who produced this recent paper –  State of Procurement Digital Transformation, Part 2: Lessons Learned By Early Adopters

The reality is that few Procurement organizations have yet realized significant value from AI. In some cases, the technology was not yet mature enough. In many, underlying data issues limited the value of early projects. According to an influential article in the Harvard Business Review earlier this year, “if your data is bad, your machine learning tools are useless.” Amy Fong, from The Hackett Group, also picked up on this in a recent webinar warning/advising for organisations to ‘get their master data in order’  That has often been the case with Procurement projects. Vodafone’s Barata pointed to an early conclusion of Vodafone’s own Smart Procurement project: the business just did not have the data quality it required to proceed. Fannie Mae’s success has hinged on its attention to data quality. “Data quality is vital,” says Fannie Mae’s Xu. “We’ve put a lot of effort into data quality, taking a field-by-field look at it to determine why we collect it, where it comes from, and what we want to do with it. When we collect data, we want to know that we can rely on it and gain insights from it.”

Companies must address Smart Procurement by implementing AI applications in parallel with efforts to ensure a solid data foundation. Complete suites built on a unified data model generate clean data and master data management solutions can address existing issues in back-end systems – for example by normalizing vendor data to support 360 degree visibility and insights. To understand more about how to get started with your own Smart Procurement projects and how to get your data ready.  Read the report Procurement Leaders: Smart Procurement Insight, in association with Ivalua.