Expanding Your Organization’s Analytic Bandwidth

Originally published September 27, 2010

Analytic talent can become your high-performance secret weapon. When taking a strategic approach to analytics, executives are finding new ways to attract and retain analytic talent, which is in scarce supply. More and more, organizations are forming competency centers and centers of excellence to achieve best practices for analytics and increase the bandwidth of existing analytic talent.
 
A strategic approach to analytics starts with executive recognition that analytics, like data, should be treated as a strategic asset. Taking such an approach requires that you analytically align along the four key organizational dimensions of people, process, technology and culture. People comprise the most important of these four dimensions. As companies grapple with where they need to best focus and use their analytic resources, we are increasingly hearing about companies doing more to better organize the analytic talent they have and cultivate a culture that values learning.
 
In his new book, The New Know , Thornton May celebrates analytic talent and describes the network of relationships it takes to realize the full value from analytics across the organization.  He encourages people to seek out quantitative modelers in their organizations to learn more about the value they are helping to create and the possibilities to do more.
 
When taking a strategic approach, analytics is a closed-loop process. Analytics can be viewed as a process in and of itself (essentially, the scientific method). The process starts with viewing data as measurements. Are you measuring what matters? Do you have the data you need to address the issue at hand? Next, you explore the possibilities of how to best model the problem, system, behavior, etc. to better inform decisions.  You are not after “the best model” as an end point. Rather, you are looking to scale better decisions across the organization, to close the loop and accelerate the process of continuous learning and improvement - all of which create value.
 
In a world where terabytes of data are available to every salesperson and line-of-business manager, many can do their own analysis but the potential for gains grows with analytical expertise—at multiple levels.  Striking the right balance between encouraging users who have access to data to do more analysis and, then, providing training and guidance to ensure they are using the tools that best complement their skill levels is another area where Analytic Centers of Excellence can help.  By empowering and challenging others to do analysis at their skill level, higher-end analytical talent can focus their attention on the more challenging issues. This will ultimately help you retain talent.  When we talk about high-end, creative problem-solving talent needed to tackle the hard problems and to identify important questions that haven’t yet been asked, these individuals are hard to find. It’s really the combination of logic, creativity and industry domain knowledge that leads to new and often better ways of doing things.  
 
Creativity is also necessary to try new things, to experiment—to sometimes fail—and learn. When we characterize someone as left-brain dominant, we think of someone like Leonard Nimoy’s character, Spock, in Star Trek. The truth is that there are many out there who are analytically savvy with well-developed, left-brain functions who also have well-developed, right-brain functions so they can  make creative analogies and approaches to formulate old problems in innovative new ways.
 
The Thornton May book also touches on the fact that many among the analytically savvy tend to be introverted and don’t tout their accomplishments, so others in the organization are often unaware of the analytical talent they have. As a result, such talent is suboptimally allocated within the organization.
 
Too often, analytic talent is found within various pockets of the organization, but it is not placed high up enough in the organization to have the visibility and impact to achieve higher levels of performance. As a result, it becomes a challenge for the analytical thinkers to span organizational boundaries and take a whole-process view. By creating a shared strategic resource, like a center of excellence (CoE), analytic talent can be more optimally allocated. This shared strategic resource is a central point to cultivate and leverage greater analytic competencies to help create more value. For example, I may be at the mercy of data coming from the call center to improve the customer experience at a key phase in the customer life cycle. If the call center data is spotty, data quality trends aren’t monitored and data collection processes aren’t improved upon for reuse in other areas, we are potentially incurring large opportunity costs. By having a shared strategic resource that takes the whole-process view, a CoE can effect change with many spillover benefits for the organization.
 
The interest in CoEs is growing across industries as organizations seek better ways to tap into their scarce high-end analytic talent to achieve greater impact. CoEs are also well-positioned to assess other options to create more analytic bandwidth. They can assess the appropriateness of the technology and if there are options to make the tools more efficient or effective, such as the following:

  • Using an environment optimized for discovery which capitalizes on our visual processing abilities.
  • Assessing new methods like variable selection, large-scale automatic forecasting and other ways of smart automation.
  • Assessing the potential for value from textual data.
  • Taking advantage of high-performance computing and grid-enabled analytics for compute-intensive optimization problems.
  • Exploring the benefits of new capabilities like in-database analytics for greater efficiencies in certain business processes.
Technology in support of agility should really be part of the deployment of analytics, enabling more people to make better decisions across the organization—not just those doing analysis and not just executives requesting analysis. Leveraging analytics strategically should inform confident decisions as efficiently and effectively as possible—from the frequently repeated operational decisions made daily to the strategic decisions at the board level.

If you need to tap into more analytic bandwidth to address problems, consider the options outside of your organization: 
  • Many projects are more tactical in nature and could be outsourced relatively easily.
  • Many new projects—and some more routine work—are well-suited to a hosted approach.  
  • Alternatively, academia is often a willing ally for research and/or student internships.
Paying attention to ensure that your creative analytic talent has a steady supply of interesting, challenging projects and offloading those that have been “figured out” is another way to ensure you can better attract and retain exceptional analysts.  This way, they know that their time is valued and that their talents are being leveraged strategically.
 
Regardless of where your organization is on its analytics journey, the analytic community within and outside your organization can be tapped into to try new things, learn faster and create more value.

SOURCE: Expanding Your Organization’s Analytic Bandwidth

  • Anne MilleyAnne Milley
    Anne, Senior Director of Analytic Strategy, Worldwide Marketing, at SAS, directs analytic strategy for global SAS product marketing. Her ties to SAS began with bank failure prediction at Federal Home Loan Bank Dallas and continued at 7-Eleven Inc. She has authored papers and served on committees for F2006, KDD, SIAM, A2010 and several years of SAS’ annual data mining conference. In 2008, Milley fulfilled a five-month SAS assignment at a UK bank. Anne is a contributing faculty member for the International Institute of Analytics.
  • Aiman ZeidAiman Zeid
    Aiman, Global Centers of Excellence Program Manager, Professional Services, at SAS, is the lead developer of SAS’ global Business Intelligence Competency Center program and services. He has 24 years of experience in information management, technical implementation of business intelligence and performance management solutions, and business consulting. Aiman also contributed to the development of SAS’ BI maturity assessment methodology and services. In addition, he has guided customers in developing and implementing a plan to maximize the business value from their technology investment, and in implementing a Business Intelligence Competency Center (BICC) to support their business objectives.



 

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