How Knowledge Analytics Works and How To Use Them

wouldn't it be cool if there was a logical progression for deploying any km approach first maybe you select and deploy desired cam tool approach you want to implement this could range from simply turning on a feature within an existing software suite to buying new capability or forming groups it could be a discussion forum a wiki you could form a community of practice or several you could introduce forms of social media like face you could pick any of these or several of these next you'd probably collect data to observe what's happening with the newly deployed tool some of these items might be metrics used to gauge success you just need to collect some stats are people using it how many people are using it other groups that aren't using it do people like it or dislike it what else should you measure and after obtaining these raw metrics you move on to another step you need to conduct a little analysis if any patterns are emerging what do the stats or metrics indicate how well is a tool being used can we measure any value added are we saving time money are we learning money are we speeding time to competency what success stories are coming out of the tool usage are there user complaints and praises regarding a tool next you might think well we've done some basic data analysis and we've looked at the metrics maybe we should think about this for a little while and do some objective critical thinking so you take your fabulous insight judgment and you look over the results to date is the km tool really adding value is it doing what it's supposed to do are there additional benefits we didn't anticipate are there unintended consequences what kind of patterns and trends are emerging what do they tell us what can we do to increase usage or enhance the approach can we collect training to help people use the tool more effectively and areas where it's underutilized can we do something to help can we address any user complaints do we need better tools in order to allow us to better analyze the value that this tool might be am adding should we even continue to use the tool or should we simply start over with another choice well after objectively and critically reviewing the data trends patterns outcomes of using the tool you either go back to step one and redeploy with changes your analysis and judgment indicator needed or you move forward to step five and you report the fabulous results of the deployment to the business and you say look how much time we save two people people look how much money we saved the company look how much money we earned for the company and while you're there standing what if the business looks back at you and says well that's great but we were actually looking to add more value in a different direction oh bummer back to the drawing board but wait what if instead of step 1 being deployment of a km tool step one was really to understand what's driving the business what if it look more like this step one is understand the business drivers you know business landscapes do have a way of changing so what is the business focus for the near term what are the business metrics to meet this year or perhaps there's a long-term strategy for which a cam approach would be a critical success factor then step two might look more like let's align our km strategy and any associated vestments with the business strategy now km will enable where the business wants to go and add the kind of specific value the business is looking for in between steps one and two we might apply a little bit of the scientific method and develop a hypothesis the hypothesis might be if we implement this particular came approach out of all the choices were most likely to line up with the business focus best then after ensuring the strategic alignment you proceed to the old step one which has now become step three then steps three four and five and six become an iterative little loop until you obtain results and see how well they match your expected outcomes and we'll call this little four-step loop a process within a process and we'll call it the km program feedback loop at the end of the scientific method we usually draw conclusions in this case it's did the cam approaches we implement it helped the business achieve the desired goals and quantify that alignment with business objectives now whether that's a yes or a No let's go back to the beginning all the way to step 1 and ensure our cam approaches continue to be aligned with business objectives thus the circle of life continues on for our knowledge management approaches this entire process is something we've lovingly come to call knowledge analytics in fact we like it so much we service marked it and what if we added knowledge analytic to the other areas often considered when applying business analytics to decision making such as workforce analytics social analytics supplier analytics etc etc and this edition of knowledge analytics improved the quality of business decisions wouldn't that be cool you

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