Procurement Expert by Gemma Howard-Sandy

The robots are coming. Except this time, they really are!

Part 1

Growing up in the 80s meant that I was convinced we'd be flying to work (if we got past 31st December 1999/ Y2K of course) and that every dog would be wearing a, "Bark to English Translator Collar" (I'm genuinely considering patenting that one). We presumed our kids would all have hover boards, that we'd be having trips to the moon and holidaying in space and that we'd all have our own 6' artificial intelligence life forms assisting us with daily life/ vacuuming.

Whilst you can now buy automated vacuum cleaners, none of the others have materialised. However, artificial intelligence (or AI), robotic process automation (RPA) and machine learning is getting ever closer.

White-collar workers have seen automation swoop in on blue collar jobs. And it could now be coming to a procurement function near you.

According to the findings of Deloitte's Global Chief Procurement Officer Survey 2018 over the past 12 months, there has been a reduction in the belief that technology will impact business in all areas except for robotic process automation (RPA). 24 per cent of CPOs believe that RPA will have a significant impact on business in the next two years, up from just 13 per cent who said the same in 2017.

Finding the right way to welcome AI, Automation and Machines into procurement, to create genuine value, could be easier said than done though.

It's probably important to provide a bit of clarity and perspective at this point, especially as I started with quite a grand look at how we perceived the 2020s to look, back in the 80s; RPA is not a physical robot. It's essentially software (or a softbot) that negates a human being from doing repetitive tasks. With rose tinted glasses on, organisations could instigate RPA within their procurement function because they want their procurement professional to spend more time engaging in growth-enhancing activities rather than time wasting within the process.

Robotics in Procurement

Before procurement roles can adjust, we need to understand how automation is currently changing the role;

  • Purchasing or Supplier Portals: Integrates category spend, portal content, products, catalogues, preferred suppliers, best suppliers for the need, and price/ contract data.
  • Portals or Management Systems: Suppliers' pricing, specifications/ SLAs and lead times/ ETAs updated in real time.
  • Order Management Systems: The ability to automatically confirm orders, with delivery dates and goods receipts speeding up the flow of goods.
  • Workflow Efficiencies: Machine learning-based purchasing approvals help to monitor and expedite approvals/ authorisation by cost code, department or user as well as spend limits.
  • Goods Receipt Confirmation: Three-way matching into a combined contract data, price data, delivery and receipt system that enables supplier-triggered payment.

RPA alone is unlikely to make you redundant. However, if your organisation started RPA integration tomorrow, and it mirrored the processes above, would you delight in your new mundane free work? Or would you struggle to fill your time? Would the next round of RPA integration then free up more time and so on? If your analysis, of how you currently spend your time, indicates that it is process tasks rather than value-enhancement activities, you must change. But the question is, what do you change to?

Bertrand Maltaverne explains, "Efficiency fuels effectiveness. Your role goes from a user of technology to the one of a manager of robots. Tech is no longer just an admin process but close to a colleague/ consultant. And, at the same time, it makes jobs more human with time freed up to focus on relationships with stakeholders and suppliers."

Strategic Sourcing and The Machine

The traditional approach to strategic sourcing helps procurement teams reduce, avoid or recover costs with their suppliers. Historical analysis of spend data can help with supplier selection but can machine learning progress beyond procurement running spend analysis reports before, during and after a sourcing event? Bertrand explained, "It can help build recommendations for the next events and detect opportunities based on more data feeds (demand predictions, market trends etc.). Learning is not just about the data in scope today, it extends to contextual aspects too."

Can a data-driven sourcing strategy carry over into the awarding of a contract etc. and can it, for instance, ensure a company is getting the best deal, regarding all parameters, departments, personnel and spend category?

The only place I can think of that our own supply chain partners provide a machine learning type experience is the analysis of spend patterns, post-event. This includes spend-to-date reports, invoice analysis, savings analysis and maverick spend analysis/ user analysis. But can this really be regarded as, "machine learning"? Or is this simply a new term for management reporting? "Yes and no", Bertrand continued, "value is to get insights, not just report. Insights could be a recommendation (like an assistant) or improvement of the algorithm e.g. learning by experience."

Risk Management and The Machine

Beyond the value measured in pounds, shillings and pence, there's a critical element within procurement: Risk. Data sources can be added on top of spend data. Users can also integrate financial risk scores, sustainability and corporate social responsibility (CSR) scores and similar third-party data sources related to risk within procurement.

With this information, procurement can enhance a spend analysis process to see not just how much it spent with a supplier but also whether that spend is in jeopardy. It could highlight if a supplier is wobbling towards bankruptcy, or if they're based in a politically unstable environment. Perhaps a trend or movement is taking place whereby a supplier's associated to an environmentally harmful production process that could potentially damage your output or reputation.

Machine learning can uncover trends within these and other key data relationships, leading to broader risk reduction and, in some cases, predictive analytics related to price and margin with suppliers. But can it do it better or more accurately than a human who's on the ball?

Bertrand explained, "With regards to risk, I think the main value from AI is related to managing more components of "risk" and in a real-time and even proactive/ predictive manner. Risks are very diverse in their nature, even more now than a few years ago. Globalisation, complex supply chains etc. are a reality that we, as people, have a hard time to grasp. Machines, however, can do that better than us. The real thing comes into perspective when you combine AI with other tech. At the end, tech is tech, the value is about insights turned into actions."

Supply Management and The Machine

Leading organisations don't just measure what they spend. They push spend analysis to incorporate their total value contribution to the business and present the business case. This allows procurement to take advantage of both traditional and newly accessible data sources to enable true supply analytics.

Getting a great deal with a supplier, based on both price and value is an aim of many procurement teams. But after a sourcing event, that supplier becomes just one of many, all of which need to be monitored and evaluated to ensure the relationship is bringing value into the organisation. I'd struggle to see how this could be replicated by AI. If suppliers and their products/ services are constantly evolving then can machine learning evolve with them without simply being "re-programmed"?

The foundational spend analysis program focuses on determining how much the business spent, with whom, in what quantity, where items were shipped/ services deployed and how they were paid. Instead of just looking at purchase orders and invoices, leading procurement teams run reports on inventory turnover and warehouse utilisation, helping them determine real inventory overhead costs and predict, "Out of Stock" status. They can also provide insights into average fulfilment times, underlying commodity costs and other overhead costs. Ultimately, spend analysis done right, helps businesses understand the total cost of doing business with a supplier. But beyond this, what could AI or RPA bring to the table that's of greater value? Time may well tell, but Bertrand explains, "Probably in building more predictive analysis, identifying anomalies and opportunities hidden in the mass of info. Why not imagine data feeds from outside of the enterprise to enrich analysis dimensions/ benchmarks?"

Part 2 Continues Here.

"Efficiency fuels effectiveness. Your role goes from a user of technology to the one of a manager of robots. Tech is no longer just an admin process but close to a colleague/ consultant. And, at the same time, it makes jobs more human with time freed up to focus on relationships with stakeholders and suppliers" - Bertrand Maltaverne

Bertrand Maltaverne

Procurement Digitalist

Bertrand Maltaverne has extensive experience in the area of procurement, and more precisely, in the impact of technology on procurement processes and organisations. He works at Ivalua as a Solutions Consultant, helping organisations achieve success in their digital transformation of their procurement practice. In previous roles he's focused on procurement technologies and processes in both direct and indirect procurement. In parallel to his professional career, he is active on various social media, and he also blogs.

Bertrand Maltaverne