If we think that everything we enjoy most was created by human intelligence, there is nothing more natural than investing in artificial intelligence, to expand human potential and improve society. That’s exactly what cognitive technology has been doing: exploring new possibilities for machines and human beings to work together and overcome previously insuperable challenges.
Considered the most important technology of our generation, artificial intelligence (AI) is the key factor in the transformation of all spheres of current life. It gave rise to virtual assistants capable of understanding and solving questions of both users and consumers, self-governing vehicles that can do without drivers and even implants that meet different needs in the human body.
More and more mature, AI is also transforming the way we view work. “We from the procurement and supply chain area have a great responsibility to bring an innovation that can provide productivity, savings, agility and collaboration”, said Luiz Gastão Bolonhez, Commercial Vice-president at Mercadoe, who has been working for 14 years in the company and for 30 years with technology.
In the business area, this intelligence can capture data to create more assertive analyses, identify opportunities and generate benefits for all involved people. And Gartner’s forecast that 85% of consumer interactions will be managed by artificial intelligence by 2020 only stresses that idea.
Artificial intelligence for Procurement 4.0
Big data, analytics, machine learning, business intelligence and cloud computing are all artificial intelligences that have created a whole new range of opportunities for businesses, thus starting the Procurement 4.0 era. According to André Kerbauy, Director of SaaS Consulting at Mercadoe, one of the greatest feats of artificial intelligence applied to the procurement area is the processing of much more data in much less time – which has allowed businesses to update their conventional procedures.
That’s the case with Spend Analysis, a process of collecting, sorting and analyzing expense data, designed to lower procurement costs, improve efficiency and monitor governance. Previously stored in spreadsheets, people used to handle this feature manually. “Now we can do such analysis with five, six, or even ten criteria to reach a conclusion”, explained Mr. Kerbauy. “With AI we can parameterize systems and algorithms, to have a wider range of criteria that can lead to real-time decisions. And what’s more, we can identify trends and standards, and minimize risks”.
From the tactical viewpoint, the reach of artificial intelligence goes equally farther for strategic purchases. “We can go beyond the mere information on orders, and have also data from contracts and invoices, to understand how these factors are linked to the country’s political and economic trends”, said Mr. Kerbauy. According to him, companies placing orders through smartphones and even by voice command is a reality already.
Another activity benefited by technology is the procurement of indirect materials, whose gains appear through negotiations. Intelligence can help by bringing, to our day-to-day buying process, the automatic quotation premium for indirect items with low negotiation potential. From parameters such as price (hard saving), inventory and freight, the system can decide on the best purchase automatically, and can even place the order.
Technology has many advantages, but how to best implement it is the question that persists in the corporate world. “The ideal choice is to implement e-procurement systems, with a usage level that covers as many purchases as possible. It’s pure change management, but it’s a real need to take one step further”, said Mr. Kerbauy.
Machines with learning ability
Among artificial intelligences, Machine Learning (ML) is an important part of a company’s innovation strategy. In addition to using all the intellectual work already produced by humans in the past, ML helps to foster decisions based on collected data directly, leading to more accurate and objective conclusions. Created in the fifties, this technology has gained more and more power due to the ability to improve its own performance without any human interaction.
One of the areas that have benefited most from machine learning improvement is Supply Chain – considered the most prominent one in the use of this artificial intelligence today. That’s what indicates a study (“Technology and innovation for the future of production: accelerating value creation”) conducted by the World Economic Forum and A.T. Kearney consulting firm; according to it, manufacturers are appraising the mix of emerging technologies to improve supply chain visibility and optimize inventory processes.
Some may even don’t realize it, but machine learning is already one of the most significant invisible forces regarding workforce allocation, expense analysis, market intelligence, risk analysis, design and analysis of sourcing events, price forecasting, and advanced contract and sourcing analysis, among other use cases.
A study from McKinsey estimates that machine learning will reduce supply chain forecast errors by 50% and lost sales by 65%, with better product availability. Supply chains are the lifeblood of most businesses. Machine learning is expected to decrease transport and storage costs, as well as supply chain management, by 5% to 10% and 25% to 40% respectively. Thanks to machine learning, it’s now possible to reduce the overall stock by 20 to 50%.
To understand how machine learning works in the real world, just think of a recurring problem in businesses: the entry of invoices. Upon receiving an invoice, the company must associate it to the order. “But when that doesn’t happen, a person will have to do the repetitive work of matching the supplier’s item to the item logged in the ERP or spreadsheet”, explained Mr. Kerbauy.
This kind of difficulty can be overcome through machine learning. “The technology will suggest these links in future activities,” said he.
Devices like APIs are another application for procurement. They are able to convey information to the user without the need for him/her to know all the contents of a contract. “These tools discover who are the people in a contract –that is, if they are suppliers, buyers or lawyers, if they are willing to negotiate, or even if contractual conditions are severe”, he added.
In the case of strategic sourcing, solutions developed with machine learning contribute to smart insights and collaboration, showing more data in real time, and promoting faster decision-making, with fewer risks among leaders. Technology allows you to send, for instance, alerts and recommendations based on what the user would do in a given situation, which in turn is based on previous transactions – everything in real time.
While agreeing on the potential of artificial intelligence to create more value for business, executives are still unsure if this is the right time to invest in technology. “Business leaders will soon realize that the basis of competition is changing. From now on, companies capable of competing with others will be the most apt ones to absorb and organize their data”, he concluded.