Spend Matters welcomes this guest post from Joe Yacura, formerly CPO of Fannie Mae, and Ken Hamilton, associate director of new growth platforms at Cognizant.
For the last two decades, source-to-pay (S2P) technology suites have emerged to provide enhanced process “efficiency,” visibility and control over global spending, as well as basic contract management and supplier risk monitoring, for both direct and indirect spend. These software platforms have helped businesses reduce costs, improve compliance and mitigate risks through data collection and analysis. They were designed to provide efficiency rather than effectiveness for the procurement function.
Efficiency comes in the form of reduced labor costs, delivered primarily by automating tactical/manual process steps. Procurement functions have advanced significantly during the last few years and new, additional responsibilities have been assigned to procurement organizations that are intended to drive sustained value in reducing supply chain cost and total cost of ownership (TCO) of procured assets. As a result, many existing ASP systems have not kept pace with “effectiveness” requirements that the procurement function must provide to better serve the business.
Purchasing organizations have at least six new challenges that weren’t present when these legacy systems were designed. These include:
- More complex processes and reporting requirements, partially driven by increased scrutiny on compliance with purchasing regulations.
- Limited access to talent with advanced analytical skills.
- Reduced decision cycle time, driven by client demands.
- Increased access to more data that needs to be analyzed and considered.
- Greater supply chain risk across a global supply ecosystems
- Additional requirements for real-time, cross-functional, cross-global, 24x7 collaboration.
New roles and challenges mean procurement teams need systems that are capable of operating at a high-level of intelligence to make real-time, autonomous decisions.
The Future State — Artificial Intelligence: Inference, Rules Engines and Cognitive Learning Tools Emerge
Current workflow applications, as sophisticated as they have become, have limitations in that they do not eliminate the need for human expertise, experience and intervention, but in fact elevate human resources to more strategic than tactical roles. They are not advanced intelligence systems. (They were designed to improve process “efficiency” and spend visibility.)
Today, sourcing leaders still have to write RFQs, generate SOWs and create negotiation strategies. Category managers still need to prepare annual strategic category plans and manage supplier risk and performance. Although the paperwork requirement and tactical components of the process have been well taken care of by these workflow applications, the goal moving forward is to integrate human knowledge and experience into these tools in a standardized way that unleash greater scale, applicability and business performance that is attainable today.
Data Science/Data-Driven Decision Making
A significant driver of the new wave of business process automation is the emergence of data science and business analytics. As social media proliferates as a communications vehicle, many companies are now inundated with massive volumes of data that require special handling, sorting and interpreting given the speed at which it is generated and the variety of types (structured, semi-structured and unstructured).
Predictive business analytics is paving the way for data-driven decision making, bringing the why factor as well as the what to light across key business processes. Today, the business analytics process is still heavily dependent on the human factor. Very soon, data management requirements will outpace the human capability. Automation will solve the immediate need for quicker reaction time, better accuracy, and improved consistency that large volumes and variety of data outputs require.
Today’s advanced knowledge system technology, when deployed, can perform these recommendations/actions currently performed by trained individuals within the company’s procurement organization. This technology can be configured to operate in a semi and/or total autonomous mode. These systems will not only reduce process cycle time, but will also assure 100% compliance with all company business rules and regulatory requirements and can operate 24x7, in real time.
Knowledge will be retained within these advanced knowledge systems and the systems will have a self-learning capability. These advanced knowledge systems will help to mitigate the risk of limited availability of individuals with advanced/specific skills. The dependence on training of individuals and knowledge transfer from the most experienced employees can be reduced as the knowledge required to perform these tasks will be harnessed and addressed by these advanced knowledge systems.
The current design of business processes will be disrupted over the next one to three years, resulting in increased operational efficiency and effectiveness. Every company will need to asses these advances and deploy advanced knowledge systems or risk their very existence. Bringing merely efficiency to the procurement function has run its course and sustainable value through improved effectiveness is now the new horizon mandate for e-procurement tools.