The Best Business Intelligence Dashboards Solve Problems

A good dash­board should iden­ti­fy trends and high­light excep­tions. But a great dash­board should incite appro­pri­ate actions that solve a prob­lem.

Larry Marine By Larry Marine from Intuitive Design. Join the discussion » 0 comments

A key tenet of UX design is that every ele­ment should incite a spe­cif­ic and desired behav­ior. What actions do most busi­ness intel­li­gence dash­boards incite? None. Sure you can drill down, but what good does that do? It cer­tain­ly doesn’t help the user rec­og­nize or solve a prob­lem.

Ahh, the ubiq­ui­tous dash­board, her­ald­ed as the great sooth­say­er of mod­ern busi­ness. But is it real­ly? Pret­ty much every busi­ness intel­li­gence dash­board I’ve seen has failed to serve its most basic and pri­ma­ry func­tion: to iden­ti­fy prob­lems and help cor­rect them. How many times have you seen a dash­board that told you where a prob­lem was or what to do about it? Prob­a­bly none. Most dash­boards show lit­tle more than sta­t­ic infor­ma­tion that tells you only that it’s work­ing. A good dash­board should do two things: iden­ti­fy trends and high­light excep­tions. But a great dash­board should also incite appro­pri­ate actions that solve a prob­lem.

Data To Action Continuum

The point of a dash­board is to help you iden­ti­fy an anom­aly and take appro­pri­ate actions. There­fore, a dash­board needs to pro­vide more than just data. It has to pro­vide action­able insights. There’s a lin­ear con­tin­u­um that ranges from data to action.

Data

Data is sim­ply a num­ber. This is the least action­able end of the con­tin­u­um. Data does not incite any action. For instance, your dash­board might show you the num­ber 12, but what does that tell you to do? This sim­ple lev­el is com­plete­ly depen­dent upon indi­vid­ual and high­ly vari­able skill lev­els of the many users. Suc­cess is as vari­able as your users’ skill lev­els.

Information

Infor­ma­tion is data with con­text, such as rel­a­tive­ness or scale. This pro­vides a lit­tle more help, but still can­not incite a spe­cif­ic behav­ior that will improve your site. This is the extent of most dash­board dis­plays and it does­n’t reduce the depen­den­cy on user skill to deter­mine what actions to take. For instance, a dash­board might show that your con­ver­sion rate is track­ing at 12 per­cent in step 3 of your 7 step con­ver­sion fun­nel. That doesn’t tell you any­thing about what to do to change that, though. More­over it does­n’t even tell you if it’s a prob­lem. Maybe 12 per­cent is actu­al­ly accept­able. But how would you know?

Insight

Insight is pro­duced by adding in addi­tion­al infor­ma­tion to help iden­ti­fy when some­thing is track­ing nor­mal­ly or not. This might include fore­casts based on cur­rent trends, indus­try aver­ages, etc. This gets you clos­er to action­able state, but still relies on the afore­men­tioned, high­ly vari­able, indi­vid­ual skills. For instance, if your dash­board dis­plays user aban­don­ment rates along your con­ver­sion flow, how do you know if those rates are a prob­lem? Con­sid­er adding com­par­i­son lines that rep­re­sent your goal and indus­try aver­ages. Then you can eas­i­ly com­pare your con­ver­sion rates to deter­mine if they are excep­tion­al or accept­able. A dash­board could even com­pare a pre­vi­ous design to a new one to deter­mine whether the new design was more effec­tive.

Action

The real goal of any data analy­sis is to iden­ti­fy a prob­lem and affect a solu­tion. Charts and graphs pro­vide sta­t­ic infor­ma­tion, but don’t sug­gest cor­rec­tive actions. This end of the con­tin­u­um requires more work to design, but ulti­mate­ly results in a dash­board that incites appro­pri­ate user behav­iors. Part of the design effort includes ana­lyz­ing poten­tial prob­lems and iden­ti­fy­ing actions that actu­al­ly cor­rect them. Exam­ple: We helped design a dash­board for phar­ma sales reps. The orig­i­nal design was pages and pages of num­bers – data. It wasn’t help­ing the reps sell any bet­ter, most­ly because sales reps are bet­ter at sell­ing than ana­lyz­ing reams of data. The desired goal of each rep was to meet their sales quo­tas in order to make their bonus­es. So we tracked pro­ject­ed sales ver­sus desired out­comes and high­light­ed if they were not going to make their bonus. We also iden­ti­fied a for­mu­la that could pre­dict sales per­for­mance based on cus­tomer vis­its and if a rep was track­ing too low, it would sug­gest that the rep vis­it spe­cif­ic cus­tomers. This design replaced pages of use­less data that required hours of analy­sis with a sin­gle page dash­board that took only sec­onds to iden­ti­fy anom­alies and cor­rec­tive actions. This dash­board design remains the indus­try stan­dard for the phar­ma­ceu­ti­cal sales domain.

Example Dashboard

Here’s a com­mon type of dash­board graph depict­ing sales per­for­mance: Dashboard example Look­ing at this dash­board, how does it answer the fol­low­ing basic ques­tions:

  • What’s the prob­lem?
  • What’s the cause of the prob­lem?
  • What can be done about it?
  • What action does this sug­gest?

Design Backwards

Typ­i­cal­ly, dash­boards are mere­ly a man­i­fes­ta­tion of the exist­ing data. The think­ing is, if we have the data, let’s dis­play it, with lit­tle regard to what you will do once you see it. But all you end up with is a visu­al­iza­tion of exist­ing data. A bet­ter approach is to start by iden­ti­fy­ing the desired out­come, such as con­ver­sion fun­nel per­for­mance and objec­tives. Then work your way back to deter­mine what data you’ll need to visu­al­ize that. Since trends or excep­tions are key indi­ca­tors that incite appro­pri­ate actions, the sys­tem will need to under­stand what are anom­alous trends or data. A com­mon way to pro­vide this is to define thresh­olds. When a data point cross­es a thresh­old, it is deemed excep­tion­al. There’s usu­al­ly a log­i­cal rea­son why it’s a defin­able thresh­old, and you can usu­al­ly relate that thresh­old to a rea­son and a poten­tial cor­rec­tive action. Thus, the more suc­cess­ful approach is to:

  • Deter­mine what goals you are try­ing to achieve.
  • Iden­ti­fy what indi­ca­tors you want to see regard­ing those goals.
  • Define the thresh­olds that dic­tate an excep­tion.
  • Deter­mine what actions you would take to cor­rect the excep­tion.
Larry Marine

Written by Larry Marine

Director, UX Design, Intuitive Design

Larry Marine earned his degree in User Experience/User Centered Design from the father of UX, Dr. Don Norman. A UX Consultant for 25 years, Larry has created some of the most successful designs on the web, including Proflowers, FedEx Print, and others. His success comes from looking at web interactions very differently, from the user's perspective. His talks, though infrequent, are often some of the most well-attended and reviewed at various conferences. His depth and breadth of experience and knowledge puts him in that rare breed often referred to as a true UX expert.

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