My 40-year career experience with BPM and analytics began after graduating with degrees in industrial engineering and operations research and with an MBA in finance and accounting. This quantitative foundation led to my first-line management job with a blue-chip conglomerate in both accounting and operations management. During my next 15 years in management consulting with Deloitte, KPMG, and EDS (now HP), I leveraged my skills in problem solving. During my last 15 years with SAS, a global leader in business intelligence, BPM, and analytics software, I have devoted my time to educating and helping organizations successfully implement BPM methodologies imbedded with analytics. As I am a careful observer of my learning environment, I have been able to author six business books, with last two being on BPM.
There is general confusion about what BPM is, and it is often perceived far too narrowly as just better financial reporting with a bunch of measurement dashboards. It is much broader than that, however. Before I clarify what BPM is and the difference between BPM and BI, I should point out that imbedding analytics of all flavors into BPM methodologies, such as correlation and segmentation analysis, enriches the BPM methodology.
BPM itself is not a new methodology, which everyone now has to learn, but rather BPM tightly integrates business improvement and analytic methodologies, which executives and employee teams are already familiar with. Think of BPM as an umbrella concept. BPM integrates operational and financial information into a single decision support and planning framework. These methodologies 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. These methodologies 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.
BPM puts BI into context. BI reporting consumes stored data that first must be cleansed and integrated from disparate source systems and then transformed into information. Analytics produces new information. BPM then leverages and deploys the information. BPM requires BI as a foundation. When analytics are added to BI and BPM, organizations gain insights for better and more timely decision making.
The greater the integration of these managerial methodologies and their seasoning with all flavors of analytics, especially predictive analytics, the greater the power of BPM. 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.
As I just described, many organizations have already begun with basic levels of BPM. Their challenge now is to move up to higher stages of maturity that include integrating BPM’s methodologies and imbedding analytics into them. A key consideration to expanding an organization’s journey is to recognize that the barriers and obstacles are no longer technical ones, but rather social and cultural. These include human nature’s resistance to change, fear of being measured and held accountable, and weak leadership. Hence, behavioral change management is a key to realizing value from BPM. A consideration for the executive team is to create a culture for metrics and analytics and to remove any fear that employees have of reprisals from what is discovered. BPM with BI is not just about monitoring the dials in a scorecard or dashboard, but rather moving the dials with integrated analytics-based methods to make better decisions.
It is a common misconception that BPM methodologies can only be applied by large companies that have the resources and budgets to implement them. As mentioned, most organizations, both large and small, are already applying methods to measure performance; calculate product and service-line profitability; plan for the future; and understand their customers. Size is not the issue. The issue is how well and robustly they perform these tasks. For smaller companies, a limitation will always be making the time and having the resources. The opportunity for them is to realize that there is substantial return on investment (ROI) from improving the ways in which they gain understanding and insights to make better decisions. BI and BPM are these ways. Applying analytics to BI and BPM no longer requires statistical experts with PhDs. Today, with analytics technology, casual users can frame and analyze problems.
What matters with any organization is the challenge in coping with complexity, uncertainty, and the rate of change. Almost all organizations see these three aspects to managing an organization as a growing concern—especially with global economics and an increasingly wired world. Therefore, there is little difference in the application of BPM methodologies between small and large enterprises.
Two major mistakes involve poor data quality and management and lack of preparation.
The first mistake is oversimplified with the phrase “garbage in, garbage out.” However, the quality and purity of the source data can either erode or improve the use of that data as information. Many BI deployments are delayed not by the technology, but by the poor state of the data that is uncovered during the implementation. Software tools like extraction, transform, and load (ETL) can solve this problem.
The second mistake involves not being prepared for adopting and implementing BI and analytics. This requires an executive leadership team that promotes learning and tolerates mistakes. Successful organizations often create competency centers where skilled employees teach and transfer knowledge to others.
A question I am frequently asked is “How do we get started?” There is often hesitation and postponement. Many organizations tend to over-plan and under-execute. My advice is to first realize there is no standard roadmap. What matters is arriving at the completion of the full vision of analytics-based BPM—BPM methodologies that are integrated with decision support methods.
Once the BI and BPM journey becomes accepted as a priority, apprehension can set in that the mountain is too high to climb. That is, there is a misconception that the systems will be enormous and take many years to implement. Getting started can be resolved by using a rapid prototyping with iterative remodeling approach. Start small but think big. Get early wins, gain lessons learned, and broaden the scope.
Initial prototype models are not intended for usable results, but rather for accelerated learning. What is engaging is that the initial models are of one’s own organization. Not only can participants relate to the models, but they can also begin to mentally connect how the information, once further refined, can be used in their analysis and decisions. They can also begin to see how the BPM models can be integrated. No model needs to be perfect and precisely accurate. Is the climb worth the view? That is, will incremental efforts to gain more detail and accuracy exceed the extra administrative effort to collect, calculate, and report the information. With discipline, users can assess when the level of detail and complexity of their models is good enough—and then move on to using the information.
SAS differentiates itself from other software vendors on three levels: (1) its application of integrated analytics; (2) its focus on business issues; and (3) its culture.
As the first differentiator, SAS has used analytics and integrated them throughout its solutions, since its foundation some 35 years ago. The company’s software was never designed nor hampered as a transactional software like an enterprise resource planning (ERP) system. SAS’s software code was originally and, continues to be, optimized to extract data and convert it into information. This allows SAS to be massively scalable with extremely fast computational power.
Second, regarding a focus on business issues, in recent years, SAS has progressed from a statistics and BI tool vendor to a solutions vendor—with many of its solutions tailored for specific industries, such as retail, financial services, manufacturing, hospitality, utilities, or oil and gas companies. Public-sector governments and universities also widely use SAS. The solutions are designed to address business issues, such as “Which customers are most attractive to retain, grow, win back, and acquire—and which are not?”
Third, from a culture basis, SAS is very unique in that its values were formed and are still guided by its founder and CEO, Dr. Jim Goodnight. The passion of Dr. Goodnight, originally a statistics professor, is to solve problems—the more difficult the better. Dr. Goodnight advocates standardization in SAS’s software code, which enables interoperability and thus allows the integration of all of SAS’s software solutions. Dr. Goodnight also insists that SAS actively listen to its customers as the source for software revisions. Roughly 25% of SAS’s $2.3 billion dollars (USD) in annual revenue goes to research and development—an order of magnitude more than other BI/BPM vendors.
You are correct. For the last two years, SAS has been selected by Fortune magazine as the #1 “Best Companies to Work For” and ranked very high in preceding years.
In my reply above, I described Dr. Goodnight as the driver of this accomplishment. SAS’s success is based on Dr. Goodnight’s directive of “trust between our employees and the company.” His belief is that happy employees will lead to happy customers. Dr. Goodnight has said, "Innovation is the key to success in this business, and creativity fuels innovation. Creativity is especially important to SAS because software is a product of the mind. As such, 95 percent of my assets drive out the gate every evening. It's my job to maintain a work environment that keeps those people coming back every morning. The creativity they bring to SAS is a competitive advantage for us."
Other factors at SAS’s headquarters include high-quality on-site child care at a reasonable monthly fee, 90% coverage of the health insurance premium, unlimited sick days, a medical center staffed by four physicians and 10 nurse practitioners (at no cost to employees), flexible dress code and work hours, a free 66,000-square-foot fitness center and natatorium, a lending library, and a summer camp for children.
In my article, I state that an obstacle to organizational improvement and strategy execution is that employees have not been granted sufficient decision rights to act on the conclusions they have derived from fact-based explorations. Decision rights remain hoarded at the top of the organization. Empowering employees with decision rights and analytical tools with which to reach those decisions is the key to organizational improvement.
Studies have shown that the two major barriers to effective strategy execution are: (1) not distributing decision rights downward into the layers of the organization chart; and (2) poor cross-functional information flows. Contrary to common belief, removing these two barriers trumps reshaping the boxes and lines in the organization chart and incentive systems. There is an iron law of economics that the better the decisions, then the better the results—and hence continuous organizational improvement will follow, financial or otherwise.
There is another obstacle. The IT function often acts as a wall between the data and its users. Experienced analysts do not use BI to search for a diamond in a coal mine or to flog the data—until it confesses the truth. Instead, they first speculate that two or more things are related or that some underlying behavior is driving a pattern to be seen in various data. They apply BI and analytics as confirmation more than as a somewhat random exploration. This requires users to have easy and flexible access to data, the ability to manipulate the data, and the software to support their processes. But IT tends to exhibit gatekeeper behavior, proclaiming, “We own the data and if you want a report, we’ll write it for you.” Progressive organizations remove this wall and train users on how to more effectively apply BI and analytics.
I do not read fiction, though I am an avid fan of the cinema. I get my business and leadership knowledge from reading articles. Books on politics capture my attention. I am an advocate of equality, which implies that unjust inequalities disturb me. The most recent book I read was Robert Reich’s Aftershock, which describes the 2008 economic global meltdown and its current effects.
Regarding my favorite place on earth, since I travel extensively for SAS, I will reply with my standard “which country do you like best?” answer. It is the Scandinavian countries of Norway, Sweden, Denmark, and Finland. Social inequalities are well managed in these countries, and the results are happy citizens with less stress.