The high popularity of the American crime drama television series, CSI: Crime Scene Investigation, is indisputable. The ratings for the original Las Vegas show and its spin-offs are proof. In each episode criminal investigators rely on physical evidence to solve murders. Since these shows are so popular, why do we not see similar zeal by organizations to sift through the mountains of data available to them to solve problems? Business intelligence (BI) and analytics software technology is quickly emerging, but why has their applications taken so long to be adopted?
The high popularity of the American crime drama television series, CSI: Crime Scene Investigation, is indisputable. The ratings for the original Las Vegas show and its spin-offs are proof. In each episode criminal investigators rely on physical evidence to solve murders. Since these shows are so popular, why do we not see similar zeal by organizations to sift through the mountains of data available to them to solve problems? Business intelligence (BI) and analytics software technology is quickly emerging, but why has their applications taken so long to be adopted?
Some believe that BI and business analytics provide a game changing competitive edge. They realize that the commonly accepted competitive strategies heralded by the strategy guru Michael Porter are now vulnerable. Porter’s main strategies are low cost leadership, product or service differentiation, and segmented customer focus. But today, all three types of strategies are defenseless against enterprising companies that can quickly lower their cost, imitate a supplier, or invade a supplier’s market space. Advocate of BI and analytics believe that the only lasting and sustainable competitive advantage comes from achieving competency by its employees with these investigative methodologies.
Fad or fashion?
As expected, whenever non-traditional techniques emerge there will be debate about their value. Some argue that simply applying data mining techniques of past outcomes is not sufficient. For example, W. Scott Evengelista, Principal of (National Life Sciences) for Deloitte Consulting LLP, observes:
“The shackles of the past (standard reports with standard data) will inevitably bind companies to increasingly failing strategies. I believe it is time leadership embraces predictive modeling to enable more effective decision making. So many companies when faced with gradual market shifts and increasing competition or strengthening barriers keep turning to old solutions and don’t recognize they are in the midst of new problems. Leadership needs to embrace the notion that analytics can help them create and find insights that will yield competitive advantage. … Leadership with many companies react so slowly to change that the companies are often in dire straits before the mandate for change comes…usually from the newly appointed CEO.”
A key term in this statement was predictive modeling. Does this mean that the magic pill will come exclusively from better crystal ball forecasting and there is less value from studying past activities and outcomes?
Rearview mirrors or the front windshield?
A popular pair of PowerPoint slides used by business conference speakers first displays a distant car behind in the rearview mirror of an automobile followed by a second PowerPoint of the same auto’s windshield view with a big oncoming truck directly in your lane – beep-beep! I am conflicted with this not so veiled message. I passionately embrace the increasing emphasis on predictive analytics and forecasting outcomes and its value to narrow the uncertainty of the future. But this implies that knowing and understanding the past is of less relative informational value than the future. There is substantial value in both views – the past and the future.
I agree with the symbolism that the rear view mirror implies that events have already happened, so they are already behind you and cannot be affected. But this message to only look forward is distorting. I personally like having rearview mirrors, and when driving I glance at them often. I want to see what types of vehicles are behind me and what rate they may be speeding up on me. There is much to be gained from analyzing trends and drawing inferences from the past.
In some cases your inference and subsequent alternative actions needs to be validated. This is where the symbolism of the windshield comes in. The ability to project what-if scenarios is powerful because then you can select the best alternative – strive for optimization.
CSI and forensics
The investigators today in business and government are analysts of all types. And today everyone can add value to their organization with an analytical mindset. Experienced analysts rely on exploration. They require easy and flexible access to data and the ability to manipulate it. They want more than data mining. To them, it is not like trying to find a diamond in a coal mine or flogging the data until it confesses. In contrast, they suspect and hypothesize that two or more things are related or that some underlying behavior is driving behavior seen in the data. They then continually test and adapt their models based on what they learn. They seek confirmation of their hypothesis.
BI and business analytics are becoming the forensic science, abbreviated as forensics, for organizational improvement. Forensics was originally the term for applying scientific methods to answer questions of interest to a legal system typically in relation to a crime or a civil action. But today forensics applies to solving an organization’s problems, exploring its opportunities, and balancing its risk appetite with its risk exposure.
If people love the CSI television series, they may likely love BI and analytics too!
Some believe that BI and business analytics provide a game changing competitive edge. They realize that the commonly accepted competitive strategies heralded by the strategy guru Michael Porter are now vulnerable. Porter’s main strategies are low cost leadership, product or service differentiation, and segmented customer focus. But today, all three types of strategies are defenseless against enterprising companies that can quickly lower their cost, imitate a supplier, or invade a supplier’s market space. Advocate of BI and analytics believe that the only lasting and sustainable competitive advantage comes from achieving competency by its employees with these investigative methodologies.
Fad or fashion?
As expected, whenever non-traditional techniques emerge there will be debate about their value. Some argue that simply applying data mining techniques of past outcomes is not sufficient. For example, W. Scott Evengelista, Principal of (National Life Sciences) for Deloitte Consulting LLP, observes:
“The shackles of the past (standard reports with standard data) will inevitably bind companies to increasingly failing strategies. I believe it is time leadership embraces predictive modeling to enable more effective decision making. So many companies when faced with gradual market shifts and increasing competition or strengthening barriers keep turning to old solutions and don’t recognize they are in the midst of new problems. Leadership needs to embrace the notion that analytics can help them create and find insights that will yield competitive advantage. … Leadership with many companies react so slowly to change that the companies are often in dire straits before the mandate for change comes…usually from the newly appointed CEO.”
A key term in this statement was predictive modeling. Does this mean that the magic pill will come exclusively from better crystal ball forecasting and there is less value from studying past activities and outcomes?
Rearview mirrors or the front windshield?
A popular pair of PowerPoint slides used by business conference speakers first displays a distant car behind in the rearview mirror of an automobile followed by a second PowerPoint of the same auto’s windshield view with a big oncoming truck directly in your lane – beep-beep! I am conflicted with this not so veiled message. I passionately embrace the increasing emphasis on predictive analytics and forecasting outcomes and its value to narrow the uncertainty of the future. But this implies that knowing and understanding the past is of less relative informational value than the future. There is substantial value in both views – the past and the future.
I agree with the symbolism that the rear view mirror implies that events have already happened, so they are already behind you and cannot be affected. But this message to only look forward is distorting. I personally like having rearview mirrors, and when driving I glance at them often. I want to see what types of vehicles are behind me and what rate they may be speeding up on me. There is much to be gained from analyzing trends and drawing inferences from the past.
In some cases your inference and subsequent alternative actions needs to be validated. This is where the symbolism of the windshield comes in. The ability to project what-if scenarios is powerful because then you can select the best alternative – strive for optimization.
CSI and forensics
The investigators today in business and government are analysts of all types. And today everyone can add value to their organization with an analytical mindset. Experienced analysts rely on exploration. They require easy and flexible access to data and the ability to manipulate it. They want more than data mining. To them, it is not like trying to find a diamond in a coal mine or flogging the data until it confesses. In contrast, they suspect and hypothesize that two or more things are related or that some underlying behavior is driving behavior seen in the data. They then continually test and adapt their models based on what they learn. They seek confirmation of their hypothesis.
BI and business analytics are becoming the forensic science, abbreviated as forensics, for organizational improvement. Forensics was originally the term for applying scientific methods to answer questions of interest to a legal system typically in relation to a crime or a civil action. But today forensics applies to solving an organization’s problems, exploring its opportunities, and balancing its risk appetite with its risk exposure.
If people love the CSI television series, they may likely love BI and analytics too!
