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IBM Deploys Advanced Analytics to Unify Its Integrated Supply Chain

"Multinational" doesn't necessarily mean global. IBM saw the need to apply rigorous analytics to virtually every function that makes up its supply chain – and in the process, harmonize business processes across the organization.

IBM Deploys Advanced Analytics to Unify Its Integrated Supply Chain

Every company wants to grow, but success has a price. Multinationals tend to morph into monsters that are difficult to tame. While the public views them as single, monolithic entities, they’re often a series of disconnected fiefdoms that can’t fully exploit the advantages of size.

So it was for many years with IBM. It consisted of multiple units that largely reflected local practices. There was no coherent approach to key disciplines such as procurement, cash collection and logistics. Redundant business units took the place of what should have been a cohesive, global effort at sourcing, collecting and delivering orders.

In the early 1990s, going through an agonizing period of self-examination, IBM began pulling itself together. It moved toward the creation of a single source of data to support demand forecasts. It consolidated purchasing power to get better deals with suppliers. And it put together the Integrated Supply Chain (ISC), with the mission of satisfying customer fulfillment on a truly global basis.

Out of that effort arose numerous projects to unify the organization. ISC came to operate in 64 countries and 80 languages. It ended up managing more than $35bn of spend for hardware, software and services acquired internally, plus some $20bn on behalf of clients.

Among ISC’s more recent efforts was the application of sophisticated analytics to the company’s “smarter supply chain.” Led by general manager and vice president Donnie Haye, it drew on individuals from IBM’s software group, consulting unit and ISC organization.

They were charged with adopting a model that included three distinct tiers: descriptive (what’s happened and is happening now), predictive (what’s going to happen) and prescriptive (what to do about it). But it was the last two categories – the heart of advanced analytics – on which they chose to focus their efforts. 

An End-to-End Effort

The project was ambitious from the start. It would be deployed across the entire supply chain, from pre-sales business processes through cash collection. The key links were defined as Opportunity to Order, Order to Cash, Plan to Deliver and Source to Pay. Together they would account for a portfolio of 30 analytics modules, including price analysis, pipeline yield assessment, critical parts management, a supply capability engine, strategic control tower, supply risk management, environmental reporting and green Sigma, to name a few.

Steven E. Bayline, senior manager of Smarter Supply Chain Analytics within the ISC, calls the initiative “the Big Play.” The idea, he said, was “to implement analytics throughout day-to-day processes.”

For example, a series of Accounts Receivables Optimization projects allow the company to evaluate cash-collection priorities and recommend to collectors the “next best action” to resolve any scenario. “This solution is increasing the productivity of our collectors while reducing our cash-to-cash cycle times,” the company said.

When it comes to internal collaboration, IBM took what it calls a “three-in-a-box” approach. The term refers to the three areas that are crucial to the success of an advanced analytics project: analytics modeling, business transformation and business execution.

Analytics modelers determine the appropriate software tools and methodologies. They work on developing proof-of-concept models, based on deep analysis of the data. Later, they engage in employee training and testing of the models.

The transformation team designs and implements the business-process changes generated by the analytics effort. It also oversees any alterations to information-technology architecture. Along the way, it develops a clear business case and project scope.

Drawing on feedback from the user community, the execution team supplies knowledge of current business processes and related data. It takes the lead on user testing, and acts as project champion during the go-live phase. 

Initiative Yields Savings

Advanced analytics has resulted in savings across the organization. Through transformation of its critical parts management and tighter collaboration with supply partners, IBM has realized $4.7m in benefits. Its buy-analysis tool has yielded cost savings of $10m. And the price-analysis module has boosted profitability by some $12m. “Within three seconds, we can provide a price quote,” said Bayline.

Another key element is a “Quality Early-Warning System,” which uses predictive analytics to anticipate a quality problem up to six weeks before it occurs. IBM combines internal data with information from the field and its extensive network of suppliers, to head off developing issues. Projected savings: $50m through 2015.

ISC learned a number of lessons along the way, the company said. Chief among them was the need to define clear objectives, the roles of each participant, and the business case for each advanced analytics project.

Even the most carefully planned initiative can fail if performance incentives aren’t aligned across internal and external organizations. IBM drew up annual performance plans, as well as precise terms and conditions for business partners, to ensure that everyone is on the same page.

In the case of the Buy Analysis tool, which recommends inventory levels and replenishment quantities, IBM promised to “price-protect” business partners’ inventory investment, provided that recommended inventory levels were maintained.

Bayline said it’s essential to focus on the readiness of users to change. “Start with a business pain point,” he said. “Have a visualization and user-interface strategy.” Transformation leadership and operations expertise are more important than math and analytics skills, he said.

An “iterative” approach to analytics allows the company to incorporate lessons learned along the way. As a result, the model is constantly being improved, allowing IBM “to start small and build toward major impact,” Bayline said.

Collaboration across the supply chain is equally vital. ISC works closely with other IBM business units such as the Software Group, Global Business Services and Global Process Services. Green Sigma, for example, is offered to clients through the IBM Tivoli product known as Intelligent Buildings Management. Analytics for outsourced procurement spend are included in the company’s SWG Emptoris product suite. And Global Business Services is commercializing several analytics modules, including the Buy Analysis tool. Other internal partners include the Smarter Supply Chain Analytics Steering Committee, and IBM Watson Research Business Analytics team.

The end result has helped tie together an organization that can now be as unified behind the scenes as it is publicly. “We’re going to continue down this transparent supply-chain route,” said Bayline. “We’re well down the road to advanced analytics today.”

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Keywords: supply chain, supply chain management, supply chain planning, supply chain analytics, IBM supply chain, high-tech supply chain, supply management, sourcing solutions, inventory control

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