‘IT and in­tu­ition work best when placed next to each other’


In a new dig­i­tal age of ‘big data’ and quan­ti­ta­tive an­a­lyt­ics, does a man­ager’s in­tu­ition mat­ter any­more? Big data is an um­brella term for solutions which were ear­lier re­ferred to as data stor­age, an­a­lyt­ics, prediction, and op­ti­miza­tion. It has gained pop­u­lar­ity to­day be­cause of the vol­ume, speed, and va­ri­ety of data be­ing gen­er­ated from mo­bile de­vices and IoT. Or­ga­ni­za­tions are evolv­ing and re­spond­ing to changes in the IT en­vi­ron­ment as new ser­vices and ap­pli­ca­tions im­prove the mar­ket. Lost in all this hype is a key fac­tor—the power of in­tu­ition.

trust your in­stincts

Re­ly­ing on in­tu­ition is a prac­tice that has driven busi­ness lead­ers to suc­cess. In­tu­ition and ex­pe­ri­en­tial learn­ing em­power you to judge the com­pet­i­tive land­scape, and un­der­stand what to look for in a prod­uct, what mat­ters to cus­tomers, and what to do with the data. There is an in­ter­est­ing the­ory that in­tu­ition is data—that hu­man in­tu­ition is pro­cessed in the ul­ti­mate black box al­go­rithm.

big data and in­tu­ition not to be seen in si­los

Surely, IT and in­tu­ition work best when placed not against, but next to each other. In­tu­ition comes into play when man­agers speak from ex­pe­ri­ence—in­sights an or­ga­ni­za­tion would miss if it spent its time star­ing at num­bers. Or­ga­ni­za­tions must con­tinue to in­vest in big data and base cru­cial de­ci­sions on it. Mean­while, the man­age­ment can en­sure IT and busi­ness ex­ec­u­tives are a part of the an­a­lyt­ics process right from the be­gin­ning. Other­wise, there is a risk of use­ful in­sights stay­ing hid­den. The ma­chines do not have all the an­swers, nor do the ex­ec­u­tives. Man­age­ment can avoid ar­gu­ments be­tween num­bers and ex­pe­ri­ence by cre­at­ing an an­a­lyt­i­cal ecosys­tem which in­cludes all the in­volved mem­bers.

find­ing a mid­dle path

The man­age­ment should un­der­stand the strengths and weak­nesses of man and ma­chine. Firstly, iden­tify the ex­clu­sive ben­e­fits each one of­fers and how the other one can take it for­ward. For this, you must also un­der­stand the lim­i­ta­tions each one comes with. For in­stance, it is a known fact that al­go­rithms work as tools, not as an end-to-end so­lu­tion. Data sci­ence is not so­phis­ti­cated enough to pre­dict whether a prod­uct will be suc­cess­ful. Ul­ti­mately, the de­ci­sion is left to in­stinct on how con­sumers will re­act to a new idea. To ask the right ques­tions, de­ci­sion-mak­ers must have a in­tu­itive un­der­stand­ing of the or­ga­ni­za­tion and its ob­jec­tives. The trick lies in know­ing when to dive into data. It re­quires an un­der­stand­ing of when and how to in­cor­po­rate man­age­rial in­stincts into data-driven de­ci­sion­mak­ing. For this rea­son, even data-driven com­pa­nies should cul­ti­vate in­tu­ition.

but you need a lit­tle se­cu­rity for big data

Or­ga­ni­za­tions are in­creas­ingly re­ly­ing on an­a­lyt­ics to make real-time de­ci­sions. Unlike in­tu­ition, even small changes in big data can have a big im­pact. This brings to fore the im­por­tance of safe­guard­ing it by de­ter­min­ing data con­fi­den­tial­ity lev­els, clas­si­fy­ing sen­si­tive data, de­cid­ing where crit­i­cal data is to be lo­cated, and es­tab­lish­ing se­cure ac­cess mod­els for both the data and anal­y­sis.

who wins?

Af­ter all, “We start with the data, but the fi­nal call is al­ways gut,” as Net­flix’s CEO Reed Hast­ings said. Thus, the days of pick­ing be­tween big data and in­tu­ition have been re­placed by the aware­ness of its merged ben­e­fits.

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