March 26, 2019
6 minutes of reading
Comments expressed by Businessmen the contributors are their own.
The following excerpt is the word Benjamin Gilad and Mark Chussilbook of New employee handbook: An unlimited view of company life. Buy it now from Amazon | Barnes & Noble | Apple Books | IndieBound Or Click here to buy it directly from us and SAVE 60% on this book as you use the code CAREER2021 through April 17, 21.
Google verbs “Big data, ”And you get 3.68 billion hits (as of June 8, 2018). See the top categories (first 10 plus paid ads) and see who is on the first page: Oracle, IBM, SAS (IBM partner), McKinsey, Informatica. Big data is Big business. Is the cost justified?
Certainly, and not at all, depending on what you expect of it.
Definitely because of common sense. Big data, along with analysis to process it, which means better, faster, more accurate forecasts and therefore better, faster, more accurate decisions. Business Press (and Oracle, IBM, etc.) can provide Big Stories, Big Anecdotes, and Big Case Studies to show how Big Data allows companies to more accurately target ads. and promotion, customer base segmentation, production and inventory planning, and a host of other applications in all internal operations from HR to marketing to R&D. Just think about it: Which one management Will it be more effective at competing, a user of guesswork and intuition or someone who uses millions of numbers to support his decisions?
The answer should be simple, but it’s not. Ironically, very little data is available about the Big Data value. We don’t know whether the emperor is wearing new clothes or sharing too much data in the open office. In one year 2012 Harvard Business Journal by MIT’s Andrew McAfee, titled “Big Data: The Management Revolution”, the author acknowledges the scarcity of good metrics of the better management revolution. He reports the results of a survey conducted by his team and McKinsey that found companies that reported using Big Data performed better. However, he also revealed that too many executives are “pretending to be more data oriented than reality”. This supports Phil Rosenzweig’s conclusion in his book, Halo effect, for similar studies of the effect of the dependent variable (performance) on the independent variable (using Big Data), making the results quite useless. As Rosenzweig has proved, several very well known studies of a company’s “formula for success” have come to fake conclusions based on this bias.
So while there is no data available on the value of Big Data, we can state that using more data and better statistical techniques can only improve management. And that’s really the problem as much as the solution. The use of Big Data and analytics has been almost entirely restricted to internal data or social media tactical information. Both belong to what Michael Porter calls “activism effective, ”But they have little or no effect on competition.
Big data doesn’t help strategy
Better management is the thing to do, and is on every executive’s mind. But this is a race with no winners and no winners lasting competitive advantage. When a Fortune 500 company uses Big Data and analytics, another company is in a hurry to do the same. At that point, other companies will fear being left behind (consultants will spread rumors that everyone else is using Big Data) and these platform vendors / consultants will maintain costs until the next productivity improvement occurs. The race will continue when all the data is big salesman Becoming very rich, just as happened with investments in information Technology. That’s exactly how capitalism must work, but it has no effect on strategic thinking … or competition.
Related: How to determine the company’s OOP
The difference between using Big Data and analytics to improve the current performance of an existing strategy versus improving the strategy itself (i.e., better competition) can be made clear by how to use an example given (ironically) by McAfee to demonstrate the value of Big Data. The article tells about how a large company improves marketing for its different brands using Big Data. The speed of the promotional cycle has been reduced from eight weeks to one! Company? Weep.
Do we need to say more?
To be fair, McAfee’s author admits that Big Data is not a substitute for the right vision and strategy (i.e., competition), but his warnings are of course a later thought. . They shouldn’t. Replacing good tactical decisions with excellent tactical decisions does not change the core of an iota company problem. Accelerating the promotion cycle is fine, but it won’t stop the ship from sinking. Identify strategic risks and strategic opportunities Soon, and acting on them before performance is impacted, that’s what matters. That is the meaning of practicing your competitive skills.
To solve this core problem, Big Data (and the analytics to turn it into intelligence) needs to move into a competitive environment with loads of high-impact players, thus helping the leader with skills. compete to outdo other players. Segmenting the razor-sharp supernatural from one’s existing unlucky customer base into micro-targeted ads won’t help at all in understanding the impact third parties have on performance and your future prospects.
Case in point: Procter & Gamble. An article in 2016 in Harvard Business Journal Out of praise for the P&G innovation engine. A McKinsey report praised its digital revolution. However, P&G, the King of Consumer Insights, has become a shadow of its own before. There’s more to competition than throwing millions of people into Big Data. Competition means capturing a whole picture.
The problem of applying Big Data to competition and other market problems translates into two simple questions:
- What are the key questions that affect how well you compete in your market?
- Do exabytes, zettabytes or hasanotherabytes help you answer those questions?
The numbers say nothing for themselves. Data is not intelligence; it’s not even analysis. It is data. Friend, The maverick, the critical, independent thinker, must find the appropriate numbers, apply the appropriate analysis, and come to appropriate conclusions.
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