Do you know how to more effec­tively man­age Big Data in 2014? In part one of this series, I only deliv­ered the first step toward more effec­tive Big Data man­age­ment, but it was a very impor­tant step: cre­ate a clear plan. Cre­at­ing a pow­er­ful, clear plan is the best way to put your orga­ni­za­tion on the path to bet­ter Big Data man­age­ment. Remem­ber, that plan should include the three key com­po­nents: data, ana­lytic mod­els, and tools. In today’s arti­cle, we will dis­cuss the next prac­ti­cal steps toward bet­ter man­ag­ing your organization’s Big Data.

Why does it mat­ter? Effec­tive Big Data man­age­ment gives orga­ni­za­tions the edge. In McK­in­sey Global Institute’s (MGI) report, “Big Data: What’s Your Plan?” they cau­tion: “Exploit­ing data is an increas­ingly impor­tant source of advan­tage. Com­pa­nies whose early efforts strug­gle risk get­ting lapped by competitors.”

Accord­ing to Har­vard Busi­ness Review’s “Com­pet­ing on Ana­lyt­ics,” what sep­a­rates the lead­ing orga­ni­za­tions from the rest of the com­pe­ti­tion in the future is an under­stand­ing and an invest­ment in the man­age­ment tech­niques avail­able today:

Ana­lyt­ics com­peti­tors under­stand that most busi­ness functions—even those, like mar­ket­ing, that have his­tor­i­cally depended on art rather than science—can be improved with sophis­ti­cated quan­ti­ta­tive techniques.”

In today’s blog, we will con­tinue with the next three steps toward Big Data man­age­ment, besides secur­ing a budget.

2 | Hire an Ana­lyt­ics Pro

Today, new titles are emerg­ing at the C-suite level.

For exam­ple, “Mobi­liz­ing Your C-Suite for Big-Data Ana­lyt­ics” reports that there are now chief ana­lyt­ics offi­cers (CAOs), chief data offi­cers (CDOs), and the ubiq­ui­tous chief infor­ma­tion offi­cers (CIOs). It was not long ago that the CIO and chief mar­ket­ing offi­cer (CMO) were the new chiefs in town. Now many orga­ni­za­tions are restruc­tur­ing and think­ing through hybrids of cur­rent posi­tions or cre­at­ing entirely new posi­tions within their struc­ture to effec­tively man­age, ana­lyze, and put their Big Data assets to good use. Where is your orga­ni­za­tion in terms of per­son­nel? Do you have any­one on staff with ana­lyt­ics knowl­edge or expertise?

Some­one within your orga­ni­za­tion needs to have work­ing knowl­edge of ana­lyt­ics, its advan­tages, ben­e­fits, and best use cases. If your CIO or CMO doesn’t have exper­tise in ana­lyt­ics, you need to con­sider hir­ing and invest­ing in some­one who does. MGI calls ana­lyt­ics “the world’s hottest mar­ket for advanced skills,” and the lead­ing orga­ni­za­tions are snatch­ing up per­son­nel with these skills sets, mak­ing them expen­sive to hire and in high demand. Another viable option to con­sider is train­ing your key C-suite level staff in ana­lyt­ics beyond the basics.

3 | Edu­cate Everyone

Just like manda­tory kinder­garten, no one in an orga­ni­za­tion should be exempt from Big Data man­age­ment and ana­lyt­ics basic train­ing today. What are the basics every­one should know? Thomas Dav­en­port, President’s Dis­tin­guished Pro­fes­sor of Infor­ma­tion Tech­nol­ogy and Man­age­ment at Bab­son Col­lege, explains:

They need to know what data are avail­able and all the ways the infor­ma­tion can be ana­lyzed; and they must learn to rec­og­nize such pecu­liar­i­ties and short­com­ings as miss­ing data, dupli­ca­tion, and qual­ity problems.”

While some of your key per­son­nel will go on to con­tinue their edu­ca­tion in ana­lyt­ics, it won’t be nec­es­sary for oth­ers. But as a min­i­mum, every­one should be “on-boarded” and given the oppor­tu­nity to become vested in this key orga­ni­za­tional change. In this case, famil­iar­ity does not breed con­tempt, it breeds oper­a­tional efficiency.

In “Big Data, What’s Your Plan?” MGI warns that unless orga­ni­za­tions “develop the skills and train­ing of front­line man­agers, many of whom don’t have strong ana­lyt­ics back­grounds, those invest­ments won’t deliver.” Spend­ing the time, money, and energy to edu­cate your orga­ni­za­tion will pay off in the long run. MGI goes on to note that as you put your Big Data plan into place, a good rule of thumb is “a 50–50 ratio of data and mod­el­ing to train­ing.” Equal parts train­ing to action and sys­tems change. The peo­ple and edu­ca­tional com­po­nent of this invest­ment is just as vital as the tech­nol­ogy and sys­tems themselves.

So call it what you want—Big Data basic train­ing, pro­fes­sional devel­op­ment days, or some­thing else entirely—but your orga­ni­za­tion must take the time to invest in a heavy edu­ca­tional com­po­nent dur­ing the period of Big Data man­age­ment sys­tems adop­tion. This will nat­u­rally cre­ate a break from oper­a­tions as usual. It will inter­rupt the daily flow and pos­si­bly, tem­porar­ily, your orga­ni­za­tional out­put, but if done prop­erly and at reg­u­larly sched­uled inter­vals, it will pay off. The invest­ment you make now to invest in your employ­ees, and the Big Data sys­tems you are build­ing will ulti­mately reap ben­e­fits in the long-term future.

4 | Con­sider Form­ing an “Uber­an­a­lyt­ics” Group

Should you cre­ate a spe­cial­ized group of peo­ple who are tasked with cham­pi­oning all-things ana­lyt­ics within your orga­ni­za­tion? Is there a more effec­tive way to spread your plan through­out the orga­ni­za­tion besides top down? Would cre­at­ing a cen­tral­ized group with inter­de­part­men­tal influ­ence be more effec­tive for affect­ing change?

Com­pet­ing on Ana­lyt­ics” cites Proc­ter & Gam­ble as an exam­ple. They cre­ated an “überan­a­lyt­ics” group of 100 ana­lysts from var­i­ous depart­ments within the orga­ni­za­tion. P&G uses the exper­tise of this group to weigh in on key issues the affect mul­ti­ple depart­ments. “For instance, sales and mar­ket­ing ana­lysts sup­ply data on growth oppor­tu­ni­ties in exist­ing mar­kets to supply-chain ana­lysts, who can then design more respon­sive sup­ply net­works.” This obvi­ously cre­ates oppor­tu­nity for greater col­lab­o­ra­tion and har­mo­niza­tion within the orga­ni­za­tion, as well as accom­pa­ny­ing challenges.

Turn Your Big Data into Action­able Data

Today, many orga­ni­za­tions have cre­ated Mobile Cen­ters of Excel­lence (MoCe) in order to stay ahead of the mobile tech­nol­ogy adop­tion curve. Now, why not take McK­in­sey Global Institute’s advice and con­sider the cre­ation of a for­mal Data Ana­lyt­ics Cen­ter of Excel­lence (DACE)? Or, at min­i­mum, take these first four prac­ti­cal steps toward turn­ing your Big Data into action­able data?