For business strategists, leaders, and decision makers are obliged to recognize propensity to accept false confirmations and/or correlations emerging from ‘big data’. It’s essential!
More business management teams are capable of rapidly processing (intellectually) substantial amounts of ‘big data’ which they presume is relevant to a (business) decision or strategy. However, the human characteristics of intellectuality and speed occasionally clash and/or not be in sync, and when they do, the potential for making, in some instances, poor – bad business decisions may rise.
To be sure, the availability and application of ‘big data’ allows many business decisions to be made efficiently and speedily and, in most instances, those are the objectives. However, when the data being relied upon for decision making omits, dismisses, or otherwise does not factor the contributory role and value of intangibles in their relevant contexts, stand by, the outcome may unnecessarily carry a higher probability for achieving something less than the desired or projected outcome.
A strategic suggestion about what business decision makers – management teams can-should do to mitigate such probabilities, i.e., their adverse impact on whether initiatives or transactions meet their expectations-projections, is to…
• distinguish the company’s intangibles that underlie – play a contributory role to company value, sources of revenue, competitive advantages, and sustainability, etc., and the decision and/or transaction at hand, and
• ensure relevant intangibles have been fully addressed – integrated in the data relied upon.
Before we delve further into decision making where speed and big data are simultaneously in play, we are obliged to possess a basic operational familiarity with the…
economic fact that today, 80+% of most company’s value, sources of revenue, competitiveness, and sustainability lie in – emerge directly from intangible assets.
So, doing both of-the-above provides business strategists and decision makers with essential context to decisions that will most assuredly contribute to business strategy and decision making to be consistently more effective especially any initiative and/or transaction in which intangible assets are-will be in play, which is a constant.
For some, this may beg the question; if – when a business strategist, management team member, or decision maker identifies an obstacle or challenge regarding their company’s operation, does it matter whether resolution paths are expressed in language or solely numerical data?
For business leaders and decision makers, recognizing the presence of personal-professional and/or data biases that may be preludes to false or misleading confirmations and/or correlations insofar as data interpretation. Left in-noticed and unchecked, either can play a not-insignificant role whether projected transaction outcomes are met, exceeded, or fail. Ultimately, recognizing (distinguishing) any receptivity for engaging in false – misleading confirmations-correlations is an important step to any business (transaction) responsibility with respect to its outcome.
Similarly, it’s important for business strategists, leaders, and management teams to demonstrate precisely how – the process they used to arrive at a decision. The reason, of course, is, if one doesn’t recognize – know what ‘thought’ steps they took and what information-data they relied on, there is virtually no way to know what ‘thought steps and data’ were not considered, overlooked, or misinterpreted.
When these practices are not in place and practiced consistently, it makes it challenging to know what questions should, weren’t, and/or remain to be asked insofar as preludes to the execution of a specific business decision and/or strategy. Too, the question business strategists are obliged to ask themselves, i.e., did the (big) data really lead to this conclusion? Or, the alternative, i.e., did the conclusion merely make the decision maker feel more successful and more comfortable, i.e., intangibles both.
According to a perspective expressed by Ken Cukier (Data Editor of The Economist, and author of ‘Big Data Is Better’) business functionality is heading to a position whereby massive amounts of (big) data are being processed and applied in ways that make people’s lives – society generally better. There will of course be some downsides. But the upsides, Cukier, and other ‘big data’ prognosticators believe, will outweigh any potential downside.
On the other hand, Susan Etlinger (big data analyst, Altimeter Group, and TED speaker) suggests the more data produced and applied presumably to make everyone and everything necessarily better off may not be quite that simple. For example, Etlinger describes an app called ‘Samaritan Radar’ that was developed in the U.K. in late 2015.
The idea underlying this app was that if a user is on Twitter and states – uses language that suggests depression and/or hopelessness, it would send an ‘alert’ to his/her Twitter followers. The alert would say something to the effect that ‘your (Twitter) friend is having a rough day today, you might want to reach out to them, and see if they’re OK’?
Such suggestive and highly subjective information, would, not inconceivably, now be available on a server somewhere, Etlinger claims. So, setting aside for the moment the ‘potential good’ such an alert and follow-up Tweet may produce, one should also ask a series of ‘what if’s’…i.e., employer sees it, their insurer sees it, clients see it, or a cyber-bully sees it; will-could adversely affect their job, health insurance, or probability of being victimized by an aggressive cyber-bully?
Etlinger is not suggesting that good things do not emerge from big data just because something bad may occur. Instead, one is obliged to consider various adverse scenarios that may manifest as we become increasingly inclined to automate the ways in which we make decisions, or how we integrate ‘big data’ into our decision-making processes.
As Guy Roz (host, TEDRadio Hour) suggests, one can certainly imagine big data being variously manipulated to purposefully harm society and people, which Etlinger follows-up by asking ‘is something essential being taken from humanity’ through more reliance and integration of big data?
What I think what we need to do, Etlinger adds, is start thinking about the ways in which technology and big data (can) serve society, all-the-while being mindful of, and perhaps design a set of principles and/or identify parameters for governing the way that technology and big data will and won’t be used and applied.
So, how should we approach big data, with a healthy amount of skepticism, and still use it for good? What a question, right?
(Parts of this post were adapted by Michael D. Moberly from a TEDSalon program held in Berlin in 2014 featuring Ken Cukier (Data Editor of The Economist, and author of ‘Big Data Is Better’.)
Michael D. Moberly November 30, 2017 St. Louis ‘Business Intangible Asset Blog’ where attention span really matters!