I’m going to run the risk of stat­ing the obvi­ous, but it’s worth remind­ing every­one that Adobe Data Work­bench is a pow­er­ful tool. Its bound­less use cases and flex­i­ble, cus­tomiz­able nature are an ana­lyt­ics practitioner’s dream. But why does that dream seem to be so stress­ful at times? Let me pro­pose the fol­low­ing the­ory: too many Adobe Data Work­bench users are focused on “mul­ti­chan­nel.” And by mul­ti­chan­nel, what I really mean is that they want as many data sources as pos­si­ble … and they want them yesterday.

Please don’t get me wrong; Adobe Data Workbench’s mul­ti­chan­nel capa­bil­i­ties are one of the many rea­sons that it is such a pow­er­ful tool. The prob­lem, as I see it, is that users place too much focus on the num­ber of data sources in a dataset, when they should be focused on the data points — or, more impor­tantly, on the qual­ity of those data points. And most impor­tantly, they should focus on the degree to which their orga­ni­za­tion is capa­ble of act­ing on the find­ings that those data points are sure to yield.

In other words, mul­ti­chan­nel is the vehi­cle that car­ries you to suc­cess, but suc­cess is real­ized in the details.

My sug­ges­tion? Don’t make “mul­ti­chan­nel” the details.

Instead, focus on cus­tomers and prop­er­ties, both online and offline. Adobe Data Work­bench will always be most effec­tive when prop­erly aligned with the over­ar­ch­ing strate­gies and objec­tives that drive your busi­ness. In fact, I would argue that with­out ensur­ing that align­ment, your orga­ni­za­tion runs the risk of encoun­ter­ing inef­fi­cien­cies as an ana­lyt­ics orga­ni­za­tion — and that is due to the very fea­tures that make the tool so pow­er­ful. In other words, with­out direc­tion, the tool’s flex­i­bil­ity and ver­sa­til­ity could lead an ana­lyst on a wild goose chase.

By fol­low­ing a log­i­cal, struc­tured process — not dis­sim­i­lar to a strate­gic plan­ning ses­sion — you’ll find your­self in a much more effi­cient state of oper­a­tions. A state that will accel­er­ate your abil­ity to real­ize value through Adobe Data Work­bench. And bet­ter yet, a state that serves as a foun­da­tion from which your ana­lysts can con­duct more cre­ative, impro­vi­sa­tional analy­sis that has a higher like­li­hood of being action­able and adding value to your organization.

In that spirit, I’ll leave you with the fol­low­ing four-step rec­om­men­da­tion for set­ting sail in the right direction:

  1. Hold a brain­storm­ing ses­sion to out­line the over­ar­ch­ing goals and objec­tives for your firm as a whole, or at least for the stake­hold­ers that you sup­port as an ana­lyt­ics orga­ni­za­tion. Remem­ber, while clichéd, no idea (or goal) is a bad idea. Writ­ing down and visu­al­iz­ing these goals will help you to think cre­atively about how your orga­ni­za­tion can pos­i­tively influ­ence the firm’s larger objec­tives. Which leads me to Step 2 …
  2. Based on those goals and objec­tives, iden­tify all of the vari­ables (cus­tomer behav­ior, mes­sag­ing, online/offline prop­er­ties, etc.) that might influ­ence the like­li­hood of your accom­plish­ing those goals. This is your stan­dard who, what, when, and where. And don’t stop at iden­ti­fi­ca­tion. Think of ways that those prop­er­ties inter­act with and influ­ence each other, and ulti­mately cre­ate cause/effect rela­tion­ships. This will help your team build com­pe­ten­cies around mul­ti­chan­nel analy­sis because it’s a dif­fer­ent exer­cise than tra­di­tional siloed, assumption-based analy­sis. As an exam­ple, how might order deliv­ery, cus­tomer sat­is­fac­tion, and/or cus­tomer ser­vice inter­ac­tions influ­ence future cus­tomer trans­ac­tions? Adobe Data Work­bench allows you to see that relationship.
  3. Match those vari­ables to the avail­able data sources/data points in your Adobe Data Work­bench pro­file, and try to iden­tify new data sources that should be added to address data gaps. This exer­cise will help pro­vide def­i­n­i­tion around the data points that are avail­able and will build con­sen­sus around the abil­ity of those data points to answer your busi­ness ques­tions. It will also open up the pos­si­bil­i­ties of acquir­ing new data from dif­fer­ent parts of the firm and sup­port cross-functional collaboration.
  4. Finally, develop Work­spaces within Adobe Data Work­bench that allow you to mean­ing­fully ana­lyze those data points in an effi­cient and impact­ful man­ner, while always ask­ing the ques­tions, “What are we pre­pared to act on?” and “What is the intended out­come of this analysis?”

Imple­ment­ing this struc­tured process can help you main­tain oper­a­tional effi­ciency by keep­ing your orga­ni­za­tion focused on data points that mat­ter. Doing so is the fastest way to real­ize the true power of Adobe Data Work­bench, which comes from help­ing you find and focus on goal-oriented data points rather than floun­der in end­less pos­si­bil­i­ties. There will always be time for adding new data sources, but you might find that you haven’t fully uti­lized the cur­rent data sources. Doing so will make for a happy bot­tom line, happy man­age­ment, and happy stakeholders.