The NOSE

LEiA: Learning Environment powered by Intelligent Analytics

During my Expert Panel discussion today at the Desire2Learn Users Conference I will introduce the concept of LEiA (named after Princess Leia), a Learning Environment powered by Intelligent Analytics.

• What is LEiA? LEiA is a framework for research, design, and development of the next generation Learning Environment powered by Intelligent Analytics.
• How does it work? LEiA is an intelligent system, dependent on a set of infrastructure services, that dynamically presents a learner with optimized learning opportunities based on who she is, where she is, the environment and situation she is in, and the people with whom she is connected.
• What does LEiA need to know about the learner? LEiA takes four input vectors to generate the optimized learning opportunity:
  
  
  • Location Awareness. Where I am: my physical coordinates.
  • Situation Awareness. The situation I am in: my context, situation, and environment.
  • Identity Awareness. Who I am: my attributes, past behaviors, learning styles, and preferences.
  • Social Awareness. Who I am with: my friends, peers, mentors, and teachers.
• What is the Intelligent Analytics part of LEiA? The Analytic Engine is the model which dynamically generates the learning opportunity ("what the learner needs") based on the four input vectors described above.

Microsoft Reverses BI Course

Microsoft continues to struggle with its Business Intelligence product strategy. The mid-tier and mass market for Enterprise Performance Management (EPM) software remains up for grabs. Microsoft seemed to have grabbed momentum with Performance Point Server (PPS) and was beginning to make inroads.  Not fast enough it seems.

Microsoft announced its intention to stop selling PPS as a stand-alone product, choosing to bundle it now with SharePoint Server (SPS). The rationale seems to be: SPS is a hot-selling product. Therefore, let's use it as the payload for introducing PPS into the small and mid-size enterprise. Microsoft needed to make a move but this is not it.

The tactic might work in the short term but will fail in the long term if Microsoft wants to upsell its BI products in the larger mid-size and large enterprise markets. I agree with analysts Sheina and Schwenk that it would have made far more sense for Microsoft to bundle PPS into SQL Server rather than SharePoint Server. Do I really want to install and contend with SharePoint Server to run analytics? The larger the enterprise the more resounding the "NO". Only time will tell.

The Year of Analytics?

Lev Gonick, CIO at Case Western Reserve University, has published his "Top 10 IT Trends for Higher Education in 2009". It's a very good list. If true, the CIO's job is getting harder, not easier. 

I have one quarrel and one comment.

My quarrel: Gonick predicts that in the category of cloud computing we will see "significant moves in the university space going well beyond cloud email services." He is particularly bullish on storage. No doubt experimentation will continue this year, but I doubt that cloud computing is ready for prime time in the enterprise. I could be wrong. If so, I would love to hear if anyone is using cloud computing in production environments for mission critical applications.

My comment: I hope that we will see significant movement this year in analytics. In his web log Mark Milliron observes that as "more accountability with less funding" becomes standard fare", one of the few strategic tools in the institution's arsenal is analytics. Will this be the year that analytics begins to get serious traction or will it continue to remain buried in the portfolio as just another project?

Scaling Innovation: An Introduction to Prahalad & Krishnan's The New Age of Innovation.

Scale matters. But when and how? For a time the theory of capitalism rested on the belief that in a competitive process large-scale capitalism always beats out the smaller counterpart. Among the first to articulate this view was Marx: "The battle of competition is fought by the cheapening of commodities. The cheapness of commodities depends, ceteris paribus, on the productiveness of labour, and this again on the scale of production. Therefore, the large capitals beat the smaller." Although the intellectual antecedents of "giantism" can be found in Marx, the theory of capitalism in the West as represented by Schumpeter, Galbraith and others in the 1950s and 1960s, also proclaimed the invincibility of the large firm. The concentration and centralization of capital leads to economies of scale, which in turn leads to the highest levels of productivity growth. Schumpeter, for example, wrote in 1942 that "What we have got to accept is that (the large establishment or unit of control) has come to be the most powerful engine of progress."

The thesis of giantism has proven to be economically suspect and historically unsound. Indeed, the pendulum has swung so far the other way that today "innovation" has become synonymous with entrepreneurship and the latent ingenuity in small firms. According to today's conventional wisdom it's the entrepreneur and the small business owner that innovates. By contrast large firms are inherently bureaucratic and sclerotic. Clayton Christensen in The Innovator's Dilemma has made the further point (in Hegelian fashion) that the very logic that drives incumbent firms to success later generates the seed of self destruction. Is there no hope then for large firms?

Prahalad and Krishnan's The New Age of Innovation is not an apologia for large-scale capitalism. However, it is one of the few recent books on innovation that approaches the problem synoptically and comprehensively. It can be read by firms small or large as a primer on innovation strategy. Their starting point is the claim that "traditional sources of competitive advantage, such as access to capital, physical location, and raw materials or technology, will become table stakes. These factors are diminishing in their importance as sources of competitive advantage. Access to these factors is becoming easier."

Value creation and new competitive advantage derive from a set of factors which Prahalad and Krishnan portray pictorially as a house. The two pillars are labelled as "N=1" and "R=G". N=1 asserts that "value is based on unique, personalized co-created experiences of customers" while "R=G" means that successful firms will draw on, though not necessarily own, ideas, talents, and resources globally. In addition to these two pillars an innovation strategy integrates business processes, analytics, technology, and social architecture. The individual elements in Prahalad and Krishnan's model are not new but their synthesis is original. Large firms need not throw in the towel just yet.

Stay tuned for more on Prahalad and Krishnan.

Top-Ten IT Issues, 2008

Educause has published its annual "Top-Ten IT Issues" of concern to technology leaders in higher education. It's not a surprise that the focus among CIOs these days is on bread and butter issues such as security, infrastructure, and identity/access management. And the ERP is the ERP and never goes away. 

The biggest surprise is what's absent from the list: Where is Analytics?

Thomas Davenport and Jeanne Harris in Competing on Analytics (it should be on the reading list of every senior leader) define analytics as: "the extensive use of data, statistical and quantitative analysis, explanatory and predictive models, and fact-based management to drive decisions and actions." In a seminal research paper and an Educause Review article ("Academic Analytics"), John Campbell and Diana Oblinger have called our attention to the potential of academic analytics to solve one of our most important challenges: "Student retention and graduation may be improved through the use of tools such as analytics, which goes beyond descriptive statistics to apply methods including predictive modeling. Already used to create a competitive edge for major corporations, analytics promises new insights and perhaps new breakthroughs in student success."

Is Analytics not on the list because our business users are getting the data they need and our organizations are building their competitive strategies around data-driven insights? We know that's not the case. Or is it that organizations simply do not have the capacity for Analytics as IT struggles to keep basic infrastructure services on track while also juggling the myriad of application balls? I believe that that's more likely the case.

We need to heed Campbell and Oblinger's call that "IT and institutional leaders need to begin to understand analytics -- as well as the changes that may be required in data standards, tools, processes, organizations, policies, and institutional culture." Let's hope that Analytics makes the Top-Ten IT Issues list for next year.

Top-Ten IT Issues, 2008

1. Security

2. Administrative/ERP/Information Systems

3. Funding IT

4. Infrastructure

5. Identity/Access Management

6. Disaster Recovery / Business Continuity

7. Governance, Organization, and Leadership

8. Change Management

9. E-Learning / Distributed Teaching and Learning

10. Staffing / HR Management / Training