June 23-26, 2013
INFORMS Healthcare 2013
October 6–9, 2013
2013 INFORMS Annual Meeting
June 10-14, 2013
Predictive Analytics World
September 8-14, 2013
2013 ASE/IEEE International Conference on Big Data
“Data science begins with data. Nothing gets built without data. Data science continues with science. Accurate, persuasive and effective prediction requires patterns. The process of discovering that pattern is science. Any product worth building requires a reliable pattern to exist in the data.”
– Christopher Berry, co-founder and chief science officer of Authintic, in his article on recommendation engines in the current issue of Analytics.
Analytics Section of INFORMS NewsInnovative Applications in Analytics Award
The Innovative Applications in Analytics Award, sponsored by the INFORMS Section on Analytics, recognizes creative and unique developments, applications or combinations of analytical techniques used in practice. The prize promotes the awareness of the value of analytics techniques in unusual applications or in creative combination to provide unique insights and/or business value.Read More
Special ArticlesBig data paying off for big companies
A new research report, “Big Data in Big Companies,” describes how 20 large firms benefit from big data projects. Report co-authors Tom Davenport of the International Institute for Analytics (IIA) and Jill Dyché of SAS, the leader in business analytics, explore how these companies have deployed analytics to generate value from their big data assets.Read More
Special ArticlesContinuing education courses for analytics professionals
The Institute for Operations Research and the Management Sciences’ (INFORMS) Continuing Education program will offer its first two courses this fall. These intensive, two-day, in-person courses will provide analytical professionals with key skills, tools and methods that can be implemented immediately in a work environment.Read More
Seeing the Future in Value Chain Management
Cisco’s strategy: Bring together formerly “silo-ed” teams around a shared nucleus of governance, metrics and culture.
Managing a global value chain for a $40 billion company is a complex challenge. Thankfully we have 9,000 colleagues to help us in our Customer Value Chain Management organization at Cisco. My role is to lead a global business operations team responsible for, among other things, strategy and planning, supply chain capability creation, ERP evolution and business intelligence across an end-to-end spectrum of disciplines that we call the customer value chain. The value chain, as we define it, goes beyond traditional supply chain management and covers everything from new product introduction and demand management through order management, sourcing, manufacturing, quality management, logistics, recycling and re-use.
We developed this holistic approach as part of a business transformation program launched at Cisco approximately five years ago. Our strategy was to bring together formerly “silo-ed” teams around a shared nucleus of governance, metrics and culture. The accelerated collaboration produced changes that have worked well for Cisco and our customers, helping us expand into new markets around the world while improving the customer experience and key metrics such as quality yields, on-time shipment and inventory turns. Today, when my boss asks for ideas on how to take our transformation to the next level of productivity and customer service, I begin my answer with two words: operations research (O.R.).
O.R., I believe, presents us with key opportunities to up-skill our organization, confirm our strategic directions and make better operational decisions every minute of every day. This has become clear, as our aspirations as a company have broadened beyond our core strength in networking equipment to encompass as many as 30 new market adjacencies. Cisco is not only expanding into new data center, virtualization and video markets; we are also reaching whole new customer segments such as home consumers making their own videos and downloading entertainment.
These new markets produce added complexity. Working with outsourced contract manufacturers and thousands of suppliers, we now design and build more than 300 major product families. Most of these products are custom-configured and built-to-order, but many now are built-to-stock. Some products need carrier-grade reliability and high-touch customer support. Others need to be localized or manufactured and shipped within legal, regulatory and tax frameworks specific to different countries, including fast-growing but uniquely demanding markets in places such as China, India, Mexico and Brazil.
In this multi-faceted environment, we no longer manage the supply chain. Instead, we are tasked to design and manage multiple high-performance global supply chains with different characteristics for multiple business models. As the mission grows more complex, and as the interdependencies among different areas of our operations continue to increase, it is becoming obvious that out-of-the-box software and conventional program management are not going to cut it. Increasingly, we are going to need hardcore statistical analyses and other advanced analytics techniques to make smart decisions on forecasting, risk management, capacity planning and many other areas across our global operations.
This optimism about O.R. is more than just academic speculation. O.R. has already made a significant impact on our value chain in areas such as demand management. Forecasting customer demand is, of course, a central part of supply chain management and a critical enabler of lean manufacturing. This discipline becomes ever more challenging in times like our own characterized by rapid changes in the macro-economy and volatile swings in supply and demand. In fact, Cisco’s need to write off some unused inventory after the dotcom bust in 2001 provided some of the impetus for the larger transformation of our value chain.
Cisco’s determination not to repeat that experience led to an initiative to establish a world-class demand management and planning capability. Constant changes in demand and our complex product mix made it clear that we couldn’t count on the forecasting models in conventional demand-planning applications. In response, we began to recruit O.R. experts and point them at the problem. They responded by developing a forecast generation process that combines advanced analytics, which are applied to enterprise data on bookings and historical demand, with a consensus process incorporating current insights from sales, marketing and finance. To generate the best possible forecast for each product line, the analytic process compares the performance of a range of methodologies over the available data. Because demand varies widely across different product lines, this ability to tailor both the data set product from our partner’s nearby factory to and the analytic methodology has enabled an airport in Malaysia, sparing our custom-Cisco to achieve significant improvements ers any disruption. over a “one size fits all” approach.
Cisco’s global value chain includes fast-growing but uniquely demanding markets such as China, India, Mexico and Brazil.
The results include better forecast accuracy, increased inventory turns and an overall improvement in supply-demand balancing that has paid off for both Cisco and our customers in the form of reduced excess inventory and faster, more reliable service. During the worst of the recent economic downturn, Cisco was able to reduce inventory in the supply chain without write-offs or a fall-off in customer service. Today, our statistical forecasting experts are working to further refine the entire process and manage the increased demand caused by the global economic recovery.
Managing risks associated with the economy, political events, natural disasters and other potential disruptions is another area where O.R. expertise is helping us transform our value chain. Analytics allow our risk management team to quantify the impact of a supply chain node being disrupted. By correlating business continuity planning data, probability data and ERP data, we can focus on those nodes that represent the highest risks to a supply chain. This helps guide our capacity planning as well as contingency plans, and we gain the ability to keep product flowing to our customers independent of world events. For example, when Bangkok’s airport was shut down by protestors in 2008, Cisco had truck convoys ready to move from our partner’s nearby factory to an airport in Malaysia, sparing our customers any disruption.
Looking ahead, many additional opportunities for O.R. exist within our value chain operations. For example, we have made good progress in implementing Six Sigma methods across our contract manufacturing and supply network, but we now have an opportunity to analyze the results of those changes to refine our future best practices and calibrate our investments. In addition, we are looking at ways to use analytics to integrate resiliency into our value chain design process. This would help us balance risks with competing objectives such as cost and flexibility.
Overall, O.R. has the potential to enable a new level of productivity in Cisco’s global value chain organization, along with an unrivaled customer experience. Analytics enable us to understand and automate an expanding list of data-intensive tasks and quickly get good answers to questions that are becoming more complex every day. How, for example, can we optimize innovation, operational excellence and customer service, driving down costs even as we make new strategic investments? With the added insights generated by O.R., we can secure competitive advantage while accelerating performance. That is a formula that pays off for our customers and our business.
Kevin Harrington is vice president of Global Business Operations in Cisco’s Customer Value Chain Management organization.