How your mar­ket­ing orga­ni­za­tion ranks in sophis­ti­ca­tion within the ana­lyt­ics capa­bil­ity matu­rity model is largely depen­dent on the level of invest­ment from the busi­ness in peo­ple, process, and prod­uct. As you review the peo­ple (mar­keters, ana­lysts, data sci­en­tists, etc.), there are other fac­tors besides job per­for­mance to con­sider as you strate­gize on the best path for improv­ing your orga­ni­za­tions’ ana­lyt­ics matu­rity. What hap­pens when you do no not have enough rep­re­sen­ta­tion from any one of these peo­ple roles? The obvi­ous answer is that your pro­gres­sion to ana­lyt­ics “Quant-dom” will be ham­pered. To make up the dif­fer­ence, some­one or some­thing has to step up and ful­fill the func­tion of the lack­ing role.

What we see across the indus­try and among our cus­tomer set is that exec­u­tives are work­ing to drive ana­lyt­i­cal matu­rity and sophis­ti­ca­tion through­out their busi­nesses. Most com­pa­nies have the abil­ity to do some descrip­tive and diag­nos­tic analy­sis, but few are able to do pre­dic­tive or pre­scrip­tive analy­sis. The chasm between the demand and sup­ply of data sci­en­tists is a well-studied and doc­u­mented cur­rent and future prob­lem. You can’t hire enough data sci­en­tists, despite your CMO’s bud­get. Our strat­egy? Empower dig­i­tal ana­lyst to do data sci­en­tist work and nat­u­rally teach the ana­lyst how to become a sci­en­tist. To bet­ter under­stand this prob­lem, the fol­low­ing rep­re­sents what I hope to be a use­ful analogy.

Think of your com­pany as a per­son who might not be as healthy as pos­si­ble. Let’s call your com­pany “Al.” In this sce­nario, Al’s friends (or in the case of your com­pany, dig­i­tal mar­keters) notice he’s not as ener­getic as he usu­ally is. After much prod­ding by Al’s friends, Al decides to visit a clinic. At the clinic, Al tells the nurse (an ana­lyst) what’s ail­ing him—he describes his symp­toms. The nurse takes his vitals to con­firm some­thing is wrong.

At this point, Al is triaged and put into an exam­i­na­tion room where another nurse asks more detailed ques­tions in an attempt to iso­late Al’s health issue. The doc­tor (data sci­en­tist) arrives, asks a few more ques­tions, and writes a pre­scrip­tion. Al’s health con­cern is addressed and (hope­fully) cured. All three par­tic­i­pants (friends, nurses, and doc­tor) worked together to get Al back on his feet.

So what hap­pens when there aren’t enough doc­tors? More to the point: What hap­pens when there are not enough data sci­en­tist to fill their role in the data ana­lyt­ics matu­rity model? This is where quants become data nurse practitioners

There’s no way to avoid going through this process if Al is going to get healthy. You can’t just look up his symp­toms on WebMD​.com and then hope that the right pre­scrip­tions will mag­i­cally appear on his doorstep. Just as WebMD is a fan­tas­tic tool for assess­ing one’s per­sonal health, the Adobe Ana­lyt­ics Capability-Maturity Assess­ment Tool (CMAT) is only a tool for diag­nos­ing a prob­lem and for pro­vid­ing sug­gested next-step rec­om­men­da­tions. Sim­i­lar to how WebMD can­not pro­vide you with pre­scrip­tions or surgery, Adobe’s CMAT will not sud­denly inject your busi­ness with “data sci­ence” so you can increase your ana­lyt­ics matu­rity. No, there still has to be a hands-on pro­fes­sional involved.

It has been pre­dicted that in the next 2 years there will be a need to hire as many as 4 mil­lion indi­vid­u­als to sup­port data ana­lyt­ics. While that sounds like good news, there is a prob­lem; there are not enough stu­dents in the pipeline to fill all these posi­tions. The end result will be ana­lysts and mar­keters tak­ing on an expanded role in the future. While you may be expe­ri­enc­ing a slight increase in blood pres­sure or anx­i­ety at the thought of expand­ing your role in this way, I hope you know that this is not a bad thing but an oppor­tu­nity. There is now room for quants, indi­vid­u­als with expanded roles and skill sets, to bloom and gain recog­ni­tion through performance.

Going back to the med­ical field, it is fairly easy to draw a few analo­gies from the chal­lenges med­i­cine has expe­ri­enced and where the future of ana­lyt­ics be over the next few years. The role of the nurse has expanded quite a bit in the last few years. Clin­ics and hos­pi­tals rely on nurses to pre-diagnose patients, apply treat­ment, and even triage patients. Doc­tors aver­age less and less time with the patient every year; there just are not enough doc­tors to go around. What’s also inter­est­ing are the increased num­ber of nurse prac­ti­tion­ers avail­able these days. A nurse prac­ti­tioner is highly trained and skilled in their field. These indi­vid­u­als could even be called “super nurses,” as they are not quite doc­tors, yet still do much of the work tra­di­tion­ally per­formed only by doc­tors. While it might be con­sid­ered an oxy­moron to place “effi­ciency” and “med­ical prac­tices” in the same sen­tence, nurse prac­ti­tion­ers have sig­nif­i­cantly increased a med­ical office’s over­all effi­ciency and ensure the doc­tors are being as effec­tive as pos­si­ble with each minute they spend in the office.

Much like nurse prac­ti­tion­ers, the ana­lyst of the future will have to become a “super ana­lyst” per­form­ing many of the tasks a data sci­en­tist would. This also means that mar­keters will have to step up their game as well. Mar­keters should be famil­iar with the ana­lyt­ics capa­bil­ity matu­rity model and where their com­pany stands within it, as well as what they can do to improve their company’s sophistication.

Think of this expanded role as the mar­keter being a par­ent who tends their child’s med­ical needs. Mar­keters must have some famil­iar­ity with the con­di­tion of their com­pany and know how to spot the early warn­ing signs of when some­thing is not right. For exam­ple, the par­ent of a child with chronic aller­gies knows how to spot the early warn­ing signs of a severe aller­gic reac­tion and how to admin­is­ter a hydro­cor­ti­sone shot or if their child needs to be taken to an urgent care clinic or ER right away. In most instances, I would even go so far as to say that it will have to be up to the data ana­lyst to train their mar­ket­ing depart­ment on how to spot issues early and how to more effec­tively self-serve using the tools at their dis­posal (e.g., Adobe Ana­lyt­ics).

Much like nurses and nurse prac­ti­tion­ers do an out­stand­ing job in lever­ag­ing a doctor’s time in the office or clinic, the ana­lyst of the future will have to bal­ance time, data, and out­put in ways that will be crit­i­cal to a company’s suc­cess. The future ana­lyst will have to triage mul­ti­ple issues, gather infor­ma­tion accu­rately and effi­ciently, and relay their find­ings in such a way that non­tech­ni­cal peo­ple can under­stand and react appro­pri­ately. Train­ing key per­son­nel within your orga­ni­za­tion, as well as under­stand­ing their spe­cific needs, is cru­cial to lever­ag­ing time with success.

For many of you in the ana­lyt­ics world, the future is now. For the rest of you, it is com­ing. Hav­ing the right tools, train­ing, knowl­edge, and pre­pared­ness in place is essen­tial. New tech­nolo­gies and processes are here and even more are on the hori­zon. What’s the first step into the future? Know­ing your company’s score of the data ana­lyt­ics matu­rity model gives you a great start­ing point.