Next Steps In Digital Procurement Transformation: More Obvious Than We Think

Constantine Limberakis

Though it may not be obvious, looking back at early experiences with emerging technology shows how we have all gone through our own personal digital transformation in recent years. I will never forget a summer BBQ in 2009 when I first used a new Apple Store app called Shazam. I recall showing the app to my friends, who were all amazed at how the app recognized the artist and song playing on the radio.

Today, interacting with AI-based digital assistants has become so second nature, we do not think twice when asking Apple’s Siri or Amazon’s Alexa for directions on the road, the latest weather forecast, or an update on the stock market. If consumer-driven experience is any indicator, these types of experiences are part of what’s leading digital transformation for procurement and the broader business.

Using consumer-led technology examples as the paradigm, software engineers and technologists are intent on finding better ways to leverage similar AI techniques in visualization and cognitive interaction for business users. While areas focused on efficiencies like robotic process automation (RPA) and blockchain take shape, placing your bets on how we interact with data and use of analytics is a natural choice for where to focus a digital transformation journey.

As an inflection point for both business users in procurement and IT professionals, advanced analytics is playing a leading role in digital transformation efforts in how emerging technologies are taking shape. According to The Hackett Group 2018 Key Issues study, the expectation for growth in these areas is in triple digits, demonstrating a keen interest in developing AI-based applications as part of the more comprehensive sourcing and procurement technology infrastructure.

Emerging digital technologies planned for the next two to three years:

Source: Key Issues Study, The Hackett Group, 2018

Early indicators of digital transformation success already point to the use of advanced spend intelligence that takes advantage of cognitive computing and machine learning for image or data recognition and detecting patterns that can provide recommendations or predictions based on spend and supply data from internal and third-party sources. Moreover, machine learning is providing immediate added value in traditional manual-intensive process areas related to vendor matching and consolidation, spend classification, price and pay anomalies, and price projections.

Adding natural language processing (NLP) and the Internet of Things (IoT), and we will soon be asking an Alexa or Siri-like procurement app questions or get interactive recommendations on what to a source, how to avoid disruption, or get the latest real-time metrics on suppliers with the worst performance or highest risk. With Amazon embedding Alexa into the Amazon app to any smartphone, putting it on Amazon Business, and the ability to send SMS text to smartphones, we are on the cusp of seeing our early personal technology experiences with AI in procurement and wider business technology.

For more on emerging technology in business, see Machine Learning And Business Problem-Solving.

Constantine Limberakis

About Constantine Limberakis

In his current role, Constantine Limberakis leads the development of intellectual property and research relating to procurement and supply chain at The Hackett Group. He has over 15 years of experience in supply management, having worked in a variety of consulting, product development, and market research jobs. He was recognized by Supply & Demand Chain Executive magazine as one of its “Pros to Know” in 2013 and 2015. Areas of procurement-related expertise include strategic sourcing, contract management, and supplier management.