Using eLearning to drive efficiency and raise your return on investment:

  raise roi ‘The study’s major sig­ni­fic­ance lies in demon­strat­ing that online learn­ing today is not just bet­ter than noth­ing — it actu­ally tends to be bet­ter than con­ven­tional instruc­tion.’ (Bar­bara Means, Inter­na­tional Depart­ment of Edu­ca­tion Report)

eLearn­ing has evolved into a remark­ably effi­cient and soph­ist­ic­ated form of train­ing deliv­ery. Yet it’s often dif­fi­cult to quantify this bene­fit in mon­et­ary terms. For those strug­gling to form­al­ise their ROI cal­cu­la­tions, Don­ald Kirk­patrick may be able to help. Since its first appear­ance in 1976, Kirkpatrick’s train­ing eval­u­ation pro­cess has grown sub­stan­tially in stature. He holds that the eval­u­ation pro­cess is divided into four levels: Reac­tion, Learn­ing, Beha­vi­oural impact and Res­ults. Ana­lys­ing all four levels can help you apply a mon­et­ary value to the effi­ciency of your train­ing cam­paign and deduce your Return on invest­ment (ROI).

Reac­tion refers to the response from those who took the eLearn­ing. Was the learn­ing exper­i­ence a pos­it­ive one? Are they await­ing their next online learn­ing ses­sion with baited breath? Have any issues or con­cerns risen to the sur­face? Was the pro­gramme as a whole embraced? Ana­lysis of this feed­back can tell you the levels of eLearn­ing accept­ance amongst a work­force, or whether they thought the con­tent was rel­ev­ant to their job. It can­not tell you, how­ever, whether the train­ing actu­ally worked.

The Learn­ing level of eval­u­ation is rel­at­ively self-explanatory. By com­par­ing the pre– and post-test assess­ments, you should be able to see a clear pos­it­ive devel­op­ment path through­out your work­force. This can also help you to determ­ine whether they have picked up the know­ledge or skills that the train­ing was sup­posed to com­mu­nic­ate. There are obvi­ous lim­it­a­tions here. You are offered only a snap­shot of the cur­rent devel­op­mental state of the work­force. There’s no way of know­ing whether the train­ing has inspired users to con­tinue their pro­gres­sion on the job or whether the learn­ing pro­cess will trail off once train­ing is complete.

That is why it is import­ant to mon­itor Beha­vi­oural change fol­low­ing train­ing. In most cases once the learner is released back into their work envir­on­ment, the eval­u­ation is com­plete. If you want to determ­ine a train­ing régime’s ROI accur­ately, it is import­ant that pre­cise beha­vi­oural data is sup­plied and then qual­i­fied in mon­et­ary terms.

Has your work­force adop­ted a new skill­set and are they util­ising it at the right moments? Are they respond­ing to scen­arios and situ­ations in the man­ner the train­ing sug­ges­ted? This kind of data can be col­lated through obser­va­tion, inter­view and follow-up assess­ments. It is then up to you to boil this data down into mon­et­ary terms that can be fed into the ROI calculation.

Finally we reach the Res­ults strand of the eval­u­at­ory pro­cess.  This seeks to estab­lish the level of improve­ment that train­ing has engendered through­out the organ­isa­tion. Did the train­ing resolve in organ­isa­tional growth?

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