Procurement has been primarily focused on buying products as directed by others, but it has had little involvement in things like strategy development and innovation. That is changing as the procurement function moves toward digitization and using insightful analytics for enhancing the organization’s supply chain and strategizing processes.
— By Betty Armstrong
The role of procurement has historically been finding the products as directed by company departments at the cheapest price. Procurement teams usually did not participate in strategic planning and innovation. Now the function is moving in the same direction as other functions by automating manual tasks and using data and analytics to streamline supply chain processes, mitigate supply chain risks, and become a full partner in organizational strategy development processes.
Forward-thinking procurement professionals are embracing ownership of digitization to achieve business goals and to drive and manage change. The challenge lies in transforming from a basic physical document data collection system where people spend most of their time responding to departmental requests to one that utilizes sophisticated digital tools to produce impactful insights that enable procurement professionals to join the organization's efforts to remain competitive through innovation and supply chain globalization.
Meeting Organizational Needs on a Higher Level
It is safe to say that most procurement functions have not changed much over the last decade, even as other functions moved to producing data analytics for intelligent decision-making.
One reason is that procurement is viewed as a "get me what I need" function rather than one that can improve end-to-end supply chains, unleash innovation through supplier relationships, and optimize the customer experience. The procurement department personnel may use a system that produces purchase orders, maintains a supplier diversity portal, and issues requests for proposals, but it probably does not use high-level analytics produced from big data, the Internet of Things (IoT), blockchain, artificial intelligence (AI), and the collaborative tools available today.
The missed opportunities that come with keeping procurement locked in the past are enormous. They include missed innovation that could flow from collaborative suppliers, increased supply chain risks and unknown cost reductions.
Bain & Co. estimates that fewer than 10 percent of procurement functions use key technologies, even though a fully automated procurement function could lower costs by up to $86 billion just for the Global 5000 companies. A non-digitized procurement function also means companies cannot be as agile and as strategic as they need to be in such a competitive global environment.
For some companies, just the thought of trying to upgrade the procurement function to take advantage of advanced technologies is overwhelming. There are also concerns about the impact of disrupting procurement and the cost compared to the ROI.
The problem is that companies failing to take the steps now toward transforming an advanced procurement function that utilizes analytics and other advanced technologies will continue to fall behind competitively because they are not extracting full value from procurement. Besides the opportunities mentioned earlier, the advanced analytics tools improve supplier negotiation tactics, identify potential supply chain issues before they become problems, and provide insights into strategic opportunities.
Moving Toward an Intelligent Process
Moving toward digital procurement is a process and not a one-time event. Some analysts say the first step is assessing the procurement function's current operation, identifying gaps or weaknesses that need closing or correction.
The reality is the first step should be building the business case for top management because top-down support is critical to ensuring the appropriate resources are committed. With top-down support and a completed assessment, analytical tools can be phased into a user interface system. They include things like spend intelligence, category analytics and bid analysis analytics.
However, this only touches the surface of digital procurement solutions. Advanced analytics also include things like predictive analytics for strategic sourcing, predicting demand with cognitive computing or AI, visualization, crowdsourcing, and informing as to costs for multiple countries. Emerging technologies include blockchain, cyber tracking, sensors for IoT, and spatial analytics.
Bringing order to structured and unstructured data is key to digital procurement because quality inputs are crucial to a successful digitized procurement system. Data comes from several sources, and it is enhanced in various ways to extract the most value.
The traditional physical data files flow from contracts, RFPs, specification sheets, bills of materials, and other procurement documents. Data is also extracted from things like cyber spend and accounts payable. Logistics data flows from movement of goods, delivery information, demand, material consumption, and receipt of goods.
There are also structured and unstructured data inputs from third parties, like supplier data, social media, commodity information, duties and tariffs, risks associated with countries, and financial processes like payment clearing.
Digital solutions are applied to the data as cognitive computing, sensors and intelligent content, improving inputs that can produce analytics and enhancing the end-to-end procurement process. As procurement digitization get more sophisticated, more value is produced via collaborative networks, advanced costing and cognitive computing, better visualization, and blockchain. The end results are predictive insights, enhanced strategy development, greater efficiency, risk mitigation in the supply chain, and improved supplier strategies.
This movement toward a digital procurement system will also enable the extraction of innovation from a collaborative supplier chain. Procurement becomes a key player in the organization’s strategic planning process for producing innovation, meeting customer needs, and improving production systems.
As mentioned, moving from legacy systems to a higher level digital system is a process. Determine the end goals, and then develop a strategy to get there through investment in technologies that expand or replace current systems.
Every company is at a different stage of technology adoption, so there is not a one-size-fits-all approach. Developing the ability to collect and manage structured and unstructured data is the first step, after ensuring automation is fully implemented. Most companies already have the ability to collect physical data files, but many would need to add unstructured data collection. Imagine a procurement function that adds external social media data to its analytics, making it possible to predict future consumer needs for better resources planning.
Once data sources are identified, the next step is implementing the tools to integrate the data to create the ability to produce intelligence. If a company already collects all data, then it could invest in technologies to improve production and use of analytics as its first step by adding tools like predictive modeling.
For all businesses, it is a journey that must begin now in order to stay competitive in the future.