Share with your friends


Analytics Magazine

Analyze This!: ‘Shareholder engagement’ keys analytics teams’ success at Cisco

March/April 2011

Vijay Mehrotra

By Vijay Mehrotra

To understand what analytics in a large organization looks like, I recently paid a visit to Cisco. I had several reasons for choosing Cisco. To work at Cisco is to live with constant organizational change, as the company has acquired and integrated 144 other firms [1] since 1993, stitching them together to form an increasingly broad set of products. The company now has more than 300 different families of products comprised of over 65,000 different parts that are produced by more than 1,000 different suppliers, with contract manufacturing partners and distribution operations across the globe.

I was also motivated by some ancient (at least by Silicon Valley standards) history. When the music abruptly stopped playing at the end of the Internet bubble, Cisco ended up with roughly $2.25 billion in unneeded parts, as its overly optimistic forecasts collided with a precipitous drop in demand. Given this history, it is certainly no surprise that (a) there is significant investment in supply chain optimization at Cisco, and (b) demand forecasting is still a big part of the action.

But, as I learned during my recent visit, to focus only on traditional supply chain analytics is to miss much of the story. Given the complexity of Cisco’s ecosystem, a huge amount of effort and investment is required just to attempt to extract value from the mountains of data captured by the company. In visiting with members of the Customer Value Chain Information and Data Strategy (CVC IDS) group (led by Anne Robinson) and their close partners from the Customer Value Chain Information Technology and Business intelligence (CVC IT BI) group (led by John Buffi), I met a diverse group of intelligent professionals who are on a journey to turn the theoretical concept of an “information value chain” [2] into a business reality.

I came away from our meeting with a sense that the mission and challenges for analytics at Cisco were much broader than I had imagined. With a combined total of just 23 people, IDS and IT BI have as their internal customers more than 9,000 knowledge workers in the Customer Value Chain Management (CVCM) organization. CVCM’s scope of responsibilities includes collaborative planning, new product introduction, sourcing and supplier management, manufacturing, order management, delivery, corporate quality and quality management, all of which adds up to a voracious need for all sorts of data and analytics.

Several themes emerged during my visit. First of all, there are a lot more resources focused on data management and data quality than I had imagined. As a fellow industrial engineer/management scientist, Robinson had warned me about this, but it was still eye opening. In my experience working in smaller organizations and consulting firms, those conducting statistical analysis and/or building mathematical models are often responsible for much of the associated data extraction, quality checking, aggregation and other “pre-processing.” By contrast, the two groups I met with featured talented BI strategists, architects and developers, enabling others in the IDS group and many more across CVCM to focus on the specifics of their analyses.

Secondly, Robinson’s group sees itself as enabling CVCM to become a more data- and analytics-driven organization. Significant time and energy is invested in supporting the effective use of data warehouses and analytic tools by people in a wide variety of roles across the broader CVCM organization, including manufacturing managers, demand planners, marketing product managers, quality specialists and process owners. These efforts include not only training and documentation but also user groups, knowledge bases and help desks. All of this is intended to increase adoption and create champions for the group’s work. Given the size and diversity of the population served by Robinson’s group, this seems in retrospect like an obvious strategic choice – but a challenging one to implement successfully, especially in a company this large and distributed. Success seems to depend heavily on the close collaboration between Robinson and Buffi’s teams.

Thirdly, there is a mindset of innovation that permeates both teams. Our discussion was sprinkled with references to plans for advanced hardware and software technologies to manage the constantly expanding needs for data across CVCM. There were also interesting discussions about innovations such as utilizing social media to disseminate information, capturing and storing data about video images, and distributing canned models and solutions to a broad population across CVCM in more efficient ways. These folks clearly spend a lot of time engaging with key CVCM stakeholders trying to understand their problems, developing and deploying prototype solutions, and getting feedback to further clarify what the business needs really are, all the while thinking of new and better ways to address them.

Finally, there is the always-important matter of senior management support. In the past, analytics professionals have often made the mistake of thinking that their funding came either by divine right (“of course our work is invaluable”) or by dumb luck (“we happened to bump into the right person and she totally ‘gets it’ ”). By contrast, these teams have been successful within Cisco because of their regular outreach across CVCM – indeed, the phrase I heard most frequently during our meeting was “shareholder engagement.” That these teams have had consistent and increasing financial support over the past three years despite the difficult economic conditions is the strongest measure of how just how much sweat equity they have built up.

At the beginning of our meeting, one of the professionals within IDS provided a brief description of how Cisco’s operations have evolved over the past two decades, growing from manufacturing operations to supply chain optimization to customer value chain management. Along with this evolution, the growth in analytics has steadily increased in size, scope and visibility. I will look forward to coming back to visit again in a few years. Based on this visit, I am confident that analytics will be thriving at Cisco for a long time to come – though I am not quite sure what the company, or the analytics groups, will look like when I return.

Vijay Mehrotra ( is an associate professor, Department of Finance and Quantitative Analytics, School of Business and Professional Studies, University of San Francisco. He is also an experienced analytics consultant and entrepreneur and an angel investor in several successful analytics companies.


  1. For a full listing of Cisco’s acquisition history, see
  2. See, for example,



Related Posts

  • 61
    Features Why optimization models fail By Patricia Randall Supply chain and manufacturing: How to avoid chaos in the field by combining simulation and real-time optimization. AI: Path to an intelligent enterprise By Joseph Byrum Imagine a future guided by artificial intelligence: Augmenting human decision-making at the enterprise level to generate…
    Tags: analytics, data, optimization, supply, chain, manufacturing, customer, work, business
  • 56
    AIMMS, a vendor of prescriptive analytics software, and Wipro Limited, a global information technology and consulting company, have joined forces in a strategic global partnership to help companies realize the benefits of advanced analytics with AIMMS-based applications.
    Tags: analytics, supply, company, optimization, chain
  • 52
    Off-site Resources Internet of Things (IOT), Cost-to-Serve, Segmentation and Supply Chain CoEs are unable to deliver promised business value without Prescriptive Analytics Is Prescriptive Analytics really going to disrupt how Supply Chains evolve? Optimizing Liberty Global’s Supply Chain: An Interview with Willem Vesters Need Robust and Flexible Supply Chain Analytics?…
    Tags: analytics, supply, chain
  • 52
    Global supply chains are constantly at risk. Natural disasters, political instability, labor shortages ... the list goes on. Leading companies are constantly evaluating how to respond to these disruptions, but only a few are really prepared to deal with the impact of trade warfare. With new import tariffs coming into…
    Tags: supply, chain, analytics, business
  • 50
    January/February Cybersecurity: new threats, new solutions The IOT and related, hidden security risks Can analytics save U.S. healthcare system? March/April Supply chain advances and solutions Software survey: vehicle routing Capitalizing on AI & machine learning May/June Social media, marketing & analytics Real-time customer personalization Next generation revenue management July/August Software…
    Tags: analytics, data, management, customer, supply, chain


Fighting terrorists online: Identifying extremists before they post content

New research has found a way to identify extremists, such as those associated with the terrorist group ISIS, by monitoring their social media accounts, and can identify them even before they post threatening content. The research, “Finding Extremists in Online Social Networks,” which was recently published in the INFORMS journal Operations Research, was conducted by Tauhid Zaman of the MIT, Lt. Col. Christopher E. Marks of the U.S. Army and Jytte Klausen of Brandeis University. Read more →

Syrian conflict yields model for attrition dynamics in multilateral war

Based on their study of the Syrian Civil War that’s been raging since 2011, three researchers created a predictive model for multilateral war called the Lanchester multiduel. Unless there is a player so strong it can guarantee a win regardless of what others do, the likely outcome of multilateral war is a gradual stalemate that culminates in the mutual annihilation of all players, according to the model. Read more →

SAS, Samford University team up to generate sports analytics talent

Sports teams try to squeeze out every last bit of talent to gain a competitive advantage on the field. That’s also true in college athletic departments and professional team offices, where entire departments devoted to analyzing data hunt for sports analytics experts that can give them an edge in a game, in the stands and beyond. To create this talent, analytics company SAS will collaborate with the Samford University Center for Sports Analytics to support teaching, learning and research in all areas where analytics affects sports, including fan engagement, sponsorship, player tracking, sports medicine, sports media and operations. Read more →



INFORMS Annual Meeting
Nov. 4-7, 2018, Phoenix

Winter Simulation Conference
Dec. 9-12, 2018, Gothenburg, Sweden


Making Data Science Pay
Oct. 29 -30, 12 p.m.-5 p.m.

Applied AI & Machine Learning | Comprehensive
Starts Oct. 29, 2018 (live online)

The Analytics Clinic
Citizen Data Scientists | Why Not DIY AI?
Nov. 8, 2018, 11 a.m. – 12:30 p.m.

Advancing the Analytics-Driven Organization
Jan. 28–31, 2019, 1 p.m.– 5 p.m. (live online)


CAP® Exam computer-based testing sites are available in 700 locations worldwide. Take the exam close to home and on your schedule:

For more information, go to