Unleashing Data Insights for All

Unleashing Data Insights for All

How to make your orga­niza­ti­on rea­dy for the ana­ly­ti­cal jour­ney

 In the era of data-dri­ven decis­i­on-making, demo­cra­tiz­ing data ana­ly­tics has beco­me a cri­ti­cal goal for busi­nesses. But what does it mean, and what should you focus on to start suc­cessful initia­ti­ves?  

Data enthu­si­ast Fre­de­rik Fritz from Stat­Soft shares some per­so­nal insights on how orga­niza­ti­ons can empower their teams and unlock the poten­ti­al of data for ever­yo­ne.  

Demo­cra­tiza­ti­on refers to making data ana­ly­tics acces­si­ble to a broa­der audi­ence within an orga­niza­ti­on. Tra­di­tio­nal­ly, data ana­ly­sis was con­fi­ned to a sel­ect group of experts – data sci­en­tists, ana­lysts and IT pro­fes­sio­nals. Howe­ver, in the light of data ubi­qui­ty, this approach cle­ar­ly has limi­ta­ti­ons: Data silos, com­plex tools and slow pro­ces­ses hin­der users to imple­ment data-based pro­ces­ses – and pre­vent orga­niza­ti­ons from using the poten­ti­al of their data.  

But estab­li­shing ana­ly­ti­cal demo­cra­cy within an orga­niza­ti­on is a jour­ney, not a sprint. While accom­pany­ing dif­fe­rent com­pa­nies in doing so in the past, and obser­ving com­mon fail­ures, I have come to iden­ti­fy a set of topics that are rele­vant for suc­cessful­ly fos­te­ring access to data ana­ly­tics for all.  

1 Gai­ning and inspi­ring trust among all stake­hol­ders  

  • Sup­port­ing data com­pe­ten­ci­es of employees: Ena­blem­ent is key  
  • Data access and trans­pa­ren­cy: Making dis­pa­ra­te sources visi­ble and acces­si­ble  
  • Data qua­li­ty and gover­nan­ce: Ensu­re that the data users work with are relia­ble. Embed them into a data archi­tec­tu­re that allows to effec­tively mana­ge and con­trol data assets.  
  • Clear goals and metrics: Defi­ne what you want to achie­ve and make goals mea­sura­ble to demons­tra­te pro­gress and deci­de about con­ti­nuing with mea­su­res.  

2 Break down bar­riers by rely­ing on com­mon grounds 

  • Defi­ned visi­on and mis­si­on: Data and ana­ly­tics initia­ti­ves need to con­tri­bu­te to over­all com­pa­ny stra­tegy.  
  • Clear com­mu­ni­ca­ti­on: Ever­y­bo­dy needs to be awa­re of what teams want to achie­ve, and how this impro­ves per­for­mance.  
  • Col­la­bo­ra­ti­on and inter­di­sci­pli­na­ri­ty: Depart­ments will bene­fit from using data sources from other fields. 
  • Pro­jects with short time­frame: Start small, with a nar­row use case. Learn and build up on expe­ri­en­ces as you go an.  
  • Crea­ti­on of col­la­bo­ra­ti­ve envi­ron­ment: Enable coope­ra­ti­on bet­ween depart­ments through set­ting shared objec­ti­ves and by inspi­ring empa­thy.  

3 Fos­ter cul­tu­ral chan­ge: Humans are at the core of demo­cra­tiza­ti­on  

  • Com­mon goals & assump­ti­ons: To break down silos you need to work with a shared frame­work of con­cepts.  
  • Par­ti­ci­pa­ti­on and inte­gra­ti­on: Ever­y­bo­dy needs to get on board. A small group of retai­ners can threa­ten a who­le initia­ti­ve.  
  • Mana­gers as role models: Not only to kick-off pro­ces­ses but to regu­lar­ly accom­pa­ny and moni­tor pro­jects and act as inter­nal sup­port­er.  
  • Trai­ning and fur­ther edu­ca­ti­on: Con­ti­nuous­ly enab­ling users will pro­vi­de them with con­fi­dence and  
  • Feed­back and adjus­t­ments: Move for­ward ite­ra­tively. Accept and learn from fail­ures and adapt lear­nings for new use cases.  

 4 Crea­te pro­tec­ted envi­ron­ment for data   

  • Sen­si­ti­se for data pro­tec­tion and secu­ri­ty: by trai­ning (and regu­lar­ly refres­hing) employees  
  • Imple­men­ta­ti­on of access con­trols: Not ever­yo­ne should have access to all data and per­form all acti­vi­ties. Defi­ne user roles and cor­re­spon­ding rights for safe usa­ge.  
  • By design & by default: Fol­low both prin­ci­ples to ensu­re maxi­mum secu­ri­ty. 
  • Data pro­tec­tion audits 

5 Choo­se to work with a com­mon ana­ly­ti­cal plat­form  

  • Tech­no­lo­gi­cal inte­gra­ti­on: It does make sen­se to ali­gn on ana­ly­ti­cal tools that are used.  
  • A com­mon lan­guage: Enab­ling data sci­en­tists to talk to busi­ness etc. Ensu­res that all stake­hol­ders can express their requi­re­ments and ide­as.  
  • Com­pre­hen­si­bi­li­ty: Ever­y­bo­dy is enab­led what is hap­pe­ning in an ana­ly­ti­cal workspace.  
  • Get star­ted fast: Intui­ti­ve (gra­phi­cal) user inter­faces allow to learn quick­ly and get star­ted with use cases and pro­to­ty­pes.  
  • Exch­an­ge: Users bene­fit from each other’s lear­nings and are able to work on issues tog­e­ther.  

Demo­cra­tiz­ing data ana­ly­tics isn’t a one-time pro­ject; it’s a mind­set and cul­tu­ral base. Orga­niza­ti­ons that embrace it will thri­ve in the data-dri­ven land­scape.  

Remem­ber, demo­cra­tiza­ti­on isn’t about repla­cing experts; it’s about enab­ling ever­yo­ne to con­tri­bu­te to data-dri­ven suc­cess. Whe­ther you’re a mar­keter, an HR pro­fes­sio­nal, or a sales­per­son, data is your ally.  

Want to learn more? Let us talk about how a plat­form like Alte­ryx suits your ana­ly­ti­cal needs!  

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Sasha Shiran­gi (Head of Sales)