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Leveraging Big Data for Efficient Procurement Decisions
By Bob Murphy, CPO, IBM [NYSE:IBM]
Challenges in Deploying Big Data Analytics for Procurement
Challenges in Deploying Big Data Analytics for Procurement
The rise of big data is fundamentally transforming the way we do business. It drives new sources of insights, intelligence, efficiency, and experience, expanding the opportunity for procurement to truly become a competitive differentiator and a value-add organization. Although everybody recognizes that data insight is critical, taking the next step and effectively leveraging it is not as straightforward as it sounds. The volume and the quality of data to harness, the complexity in defining the right governance around that data, and the new skill set required for procurement teams to be able to handle and extract value from it are among the 3 biggest challenges facing organizations.
“Fuelled by analytics, procurement can derive insight from disparate sources of information and uncover intelligence for competitive advantage”
Data Volume and Quality
Organizations, now more than ever, are faced with a plethora of data to interpret; 80 percent of that data is unstructured, generally untapped, and growing in volume exponentially, at an almost un-sustainable pace. The usability of the data in terms of selection, extraction, and storage, as well as quality and relevance are also significant considerations. That said, today cognitive technology is leveraging artificial intelligence and demonstrating ability to ingest data and continuously learn as humans would on an enormous scale. Cognitive technology now brings the capability to analyze all (even unstructured) data, and can understand its meaning, reason, generate hypotheses, arguments and recommendations from which procurement professionals can make more informed decisions. It will provide the capability to automate strategic sourcing tasks, such as RFx creation, analysis, and even scoring, including a level of complexity that can’t be handled by humans on the same scale, nor in the same timeframe. In the near future, even market research and negotiations will be improved, sped up, and handled by technology in an even more efficient manner.
Governance for Data
Another challenge is the ownership question. Who should be responsible for, own and manage big data? Lack of clarity on this makes the deployment more complicated and less efficient. If procurement wants to take a more active role in value creation as a trusted business partner, it needs to take a more active role in owning relevant data sets, driving the agenda for big data beyond the context of receiving it from another business function. With this in mind, I decided to appoint a Chief Data Officer, reporting to me directly, to look across the source to pay framework. The CDO looks at our analytical solutions and establishes a strategy on how to gain the most traction from analytics. Our vision for analytics and the project roadmap have us progressively managing data from many different sources in order to provide rich insight that is not only advanced but at the right place, right time and fit for purpose. It is this analysis and leveraging of varied data sources that provides insight not otherwise available or too complex to understand and process without the appropriate tools and analytic capabilities. Today at IBM we have reached 90 percent hands-free transactions. We are also building on existing processes and functionality to effectively influence client decisions by directing end users to more cost effective and/or preferred solutions. The objective is to facilitate improved supplier negotiations and generate additional cost reduction opportunities.
The New Skill Set for Procurement
Undeniably, the function needs to get ready and start considering how it will transform its role and skill set. Procurement is facing some skill gaps when it comes to handling big data analytics. Harnessing data and being able to glean useful insight from it requires new skills, such as ability to identify patterns, trends with machine learning algorithms, or to apply statistical models to large-scale data to better identify opportunities. It means that procurement professionals need to develop these skills in addition to augmenting staff through recruiting.
Deploying big data analytics presents some organizational and technology challenges and opportunities for procurement, not only in defining and delivering a new agenda but also on how to really take advantage of the opportunity data insight brings. Embracing a cognitive approach provides the ability to process large amounts of data and represents a key stepping-stone for procurement organizations if they want to stay relevant to the business and successfully differentiate themselves. With the right strategy, structure, skill set and cognitive technology, the procurement function is best placed to thrive and demonstrate its value to the organization.
Fuelled by analytics, procurement can derive insight from disparate sources of information and uncover intelligence for competitive advantage. This paves the way for us to develop an even deeper understanding using cognitive technologies that will help us further transform the procurement landscape as we engage across our supply base and with business partners to unlock value from all types of data that have been hidden in the past.