What did I do?
The topic in the syllabus was much smaller this week and is perfectly summarized in the introduction paragraph. So far, we had be mainly seeing examples of point solutions for specific courses or small portions of the organization.
...Greatest impact, however, will be when analytics are integrated (integrated Knowledge and Learning Analytics Model - iKLAM) and planned at a systemic level. ... Reducing barriers to information flow is important for systemic-level analytics.I listened to the replay of Linda Baer's session. As my focus is on corporate and not educational institutions, I 'took note' of what is happening, but I rather skimmed through the papers and discussions. Here is one of her slides that I have seen somewhere before. It's a nice overview of how an organisation can grow from 'let's have lots of reports' to more strategic and more systemic and integrated levels of analytics. You can use this as a growth path or maturity model for analytics.
I forgot in which assigned reading or recording, but the author did reveal the 'factory approach' to education with the statement "... we have to PRODUCE 16 million more graduates... ". No further comment on that.
I also watched some videos of the Strata conference, like the one below. I noted the 'digging for gold in the big stream of data' analogy in Mark Madsen's video. It does feel like we are digging for gold but haven't figured out exactly where the gold is... I also noted that for most businesses today, business intelligence sadly means reporting. (Which bring us back to the chart above to move up the competitive advantage levels).
The topic for this week reminded me of a paper we made at IBM on the future of learning in education. It talks about an education continuum that stretches not only over the different stages of education (integrated flow from kindergarten to university) but into labor market needs and government focus and its priorities. I see data flows and analytics as an enabling instrument for linking these former islands into one big education continuum. Equally, I see (open) data flows and analytics as a key enabler for linking business silos as the training department, the other HR functions such as performance management and recruiting, business needs and even business partner relationships.
What sense did I make of it all?
Future and action: What should be the the focus? By nature of the education beast a lot of the excellent work that happened in institutions and research is focused on analyzing the past without any intent to learn anything for the future. The corporate beast is much more cruel: any analytics we get to carry out MUST be focusing on the future and have the potential for (corrective) action in them. As far as the corporate mindset is concerned, the past is done. The past is reflected in the quarterly revenue numbers and on the stock exchange.
Once again I went over some case studies that predict failure in getting an educational degree. This seems one of the most mature areas of today's application of learning analytics in institutions. That makes a lot of sense too, as it is a crucial worry that governments have and one that goes directly into optimizing where taxpayer's money goes. The area of failure prediction or signaling however cannot really be used as such in a corporate setting. A degree or test result is not the goal there, and very few corporate learning programs are actually designed so one can realistically fail. But if we could use the same techniques to predict performance, and predict the outcome of a specific training program on performance of an individual, we have a winner.
A few of our corporate programs like the Global Sales School make use of performance dashboards within the learning program. I think that's a good first step of linking performance analytics to training.
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