Over the years, Gary Cokins has provided advice and direction with his thought-provoking insights, sometimes presented in a playful, tongue-in-cheek manner. He has written 100 columns for Information-management.com, and whether he’s writing a letter to the CEO, pitching a new TV game show, comparing organizational roles to animal species or calling us to embrace analytics, Cokins' depth of knowledge, passion for analytics and performance management, and warm personality (not to mention his love of baseball) shine through in his writing. The result is a loyal following of readers and rich archive of wisdom from a respected industry thought leader.
Information-Management.com Editor-in-Chief Julie Langenkamp-Muenkel talked with Cokins about his career, perspective on analytics and performance management and what drives him in his work.
Information-Management.com: Gary, you have a rich history in the analytics and enterprise and corporate performance management space. How did you get into it?
Cokins: My 40-year career experience with analytics and enterprise and corporate performance management methods began after receiving a BSc degree in industrial engineering/operations research from Cornell University in 1971 and an MBA from Northwestern University’s Kellogg School of Management in 1974. This quantitative foundation led to 10 years as a first-line manager with a blue-chip manufacturing conglomerate as a financial controller and the operations manager. During my next 15 years in management consulting with Deloitte, KPMG and EDS (now HP), I leveraged my skills in problem solving. At age 64 I recently retired from SAS, a global leader in business intelligence and analytics software, after 16 fun years there. With SAS I educated and trained organizations to successfully implement EPM/CPM methods imbedded with analytics. [By the way,] EPM and CPM are synonymous, so for the remainder, I will refer to them as only EPM.
There was some career luck and circumstances that led me to the field of EPM. In 1988, KPMG consulting established a partnership with Harvard Business School Professor Robert S. Kaplan to implement activity-based costing systems. I was recruited to KPMG based on my skills. As a result of my practitioner experiences, I wrote three books about ABC, then as I broadened I wrote subsequent books about EPM. I present at conferences and write blogs and articles. It has been a privilege to have written 99 consecutive monthly articles since 2004 for www.information-management.com and build relationships with readers.
Why are you passionate about the industry?
My passion for EPM and analytics is in large part due to the personal satisfaction I feel when I help others improve and add value. This assistance and guidance can be for organizations or individual employees and teams – especially those exhibiting “champion” behavior. My observation is that although it is ideal to have executive sponsorship for new projects and methods, often executives are distracted with fire-fighting and short-term priorities. I enjoy empowering champions who want to improve their organizations. I have seen the successful outcome of EPM systems I have helped implement with substantial tangible results. I get pleasure knowing I made an impact.
With your aim of helping champions improve their organizations, I imagine you need to do some educating and evangelizing. How do you define enterprise performance management?
There is general confusion and lack of consensus about what EPM is, and it is often perceived far too narrowly as just a CFO function’s initiative for financial reporting with a bunch of measurement dashboards. It is much broader than that, however. EPM itself is not a new method which everyone now has to learn, but rather EPM is the tight integration of several business improvement and analytic methods, which executives and employee teams are already familiar with. The problem is that systems are typically implemented in isolation of each other or in a sequence. There is more synergy and power when they are all integrated.
Think of EPM as an umbrella concept. EPM integrates operational and financial information into a single decision support and planning framework. These methods include strategy mapping, balanced scorecards and dashboards, customer profitability analysis (using activity-based costing principles), forecasting, driver-based budgeting with rolling financial projections, and resource capacity requirements planning. Most of these methods have been in existence for decades, and many even before there were computers. What makes them relevant now is the need to integrate them for faster decisions to more complex problems and opportunities. The EPM methods in turn fuel other core solutions, such as customer relationship management, supply chain management, risk management, and human capital management systems, as well as lean management and the Six Sigma initiatives. It is quite a stew, but they all blend together. Embedding analytics of all flavors into EPM methods – such as correlation, clustering and segmentation analysis – enriches each of EPM’s many methods.
Two of the pervasive themes in your writing center on BI and analytics. Would you explain the difference between business intelligence and analytics?
Here is my simple view to answer your question. Business intelligence reporting consumes stored data that first must be cleansed and integrated from disparate source systems and then transformed into information. Analytics produces new information from the originally stored data. EPM’s various methods then leverage and deploy the information. In effect, the EPM suite of methods puts BI into context.
The EPM methods require BI as a foundation. When analytics are added to BI and EPM, organizations gain insights for better and timelier decision-making.
The greater the integration of the EPM managerial methods and their seasoning with all flavors of analytics, especially predictive analytics, the greater the power of EPM. Predictive analytics are important because organizations are shifting from managing by control and reacting to after-the-fact data toward managing with anticipatory planning so they can be proactive and make adjustments before problems arise. Predictive analytics also reduce the uncertainty of key independent variables, such as sales unit demand volume, from which many other dependent variables, such as cash flow and work force headcount, can be modeled and calculated.
So much has changed in IT, BI, analytics and EPM since you began writing for us in 2004. What’s your view of the way the industry has evolved, and what excites you about the current marketplace?
I view two related but separate aspects on how the IT, BI, EPM, and analytics have evolved: technology and behavioral change management.
The technology acceleration is amazing. For some perspective, I recently became aware that Facebook, Twitter, 4G, iPhones, iPads, high-speech broadband, ubiquitous wireless and Web-enabled cellphones, the cloud, cell phone apps and Skype did not exist or were in their infancy a decade ago. They have all substantially “evolved” since I wrote my first Information-Management.com article in November 2004. Everyone can see the effect of big data – more volume, variety and velocity – on analysis and decision support. Everyone sees the shift to mobile tablets and smartphones. This evolution excites me as a spectator in the stands watching it happen.
But what excites me more than advances in technology are the organizational culture and behavior considerations that will challenge almost all organizations. My belief is that technology is no longer the impediment and obstacle it once was for organizations to embrace the pursuit of “optimization.” What is now slowing the adoption rate of applying analytics and realizing the full vision and value from EPM methods are people. And this is understandable. It is human nature to resist change. People naturally like the status quo. It is safe and familiar. Most people do not care to be measured or held accountable, especially when factors that they may be judged by are out of their control. Today I write and speak more on these soft skill aspects than the hard skills needed to build EPM and analytics models. I enjoy advising individuals and organization on how to get buy-in to move faster – speed to results.
What are the most important aspects of analytics today?
Analytics is becoming a competitive edge for organizations. Once considered “nice-to-have,” applying analytics, especially predictive business analytics, is now becoming mission-critical. The use of analytics that include statistics is a skill that is gaining mainstream value due to the increasingly thinner margin for decision error. There is a requirement to gain insights, foresight and inferences from the treasure chest of raw transactional data (both internal and external) that many organizations now store (and will continue to store) in a digital format.
There is always risk when decisions are made based on intuition, gut feel, flawed and misleading data or politics. One can make the case that increasingly the primary source of attaining a competitive advantage will be an organization’s competence in mastering all flavors of analytics. That is, it may be that the ultimate sustainable business strategy is to foster analytical competency and eventually mastery among an organization’s work force. If your management team is analytics-impaired, then your organization is at risk.
Today managers and employee teams do not need a doctorates degree in statistics to investigate data and gain insights. Commercial software tools are designed for the casual user.
As you contemplate topics for your next 100 columns for us (laughs), what do you think will be big in the near and long-term future?
Many now see the game-changer of in-memory chips with massive lightning speed computing power and the explosion of sensors that will collect data on virtually everything.
Much of your writing stems from what you’ve learned throughout your career. What advice do you have for people in our industry looking to establish lasting, meaningful careers?
My advice to any professional of any age with skills in IT or analytics is to demonstrate leadership. I do not mean leadership as being an executive at the top of the organization chart. I mean exhibiting leadership by being more than just a support to colleagues who make decision and leading by engaging and motivating others.
My belief is that the three primary success factors for effective leaders are technical competence, critical thinking skills and communication skills. For the analyst as a leader, three personal quality characteristics are needed: curiosity, imagination and creativity. The three are sequentially linked. Curious people constantly ask “Why are things the way they are?” and “Is there a better way of doing things?” Without these personal qualities then innovation will be stifled. The emergence of analytics is creating opportunities for analysts as leaders.
Thank you, Gary, for sharing your wisdom and insights with us. Congratulations on reaching this milestone of 100 columns published with Information Management.
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