New site, new organization

I have not had much time to update this blog recently.  Work has been busy.  I have also been working on a new way of organizing my blogging entries.

One of the things I am doing is migrating off wordpress.com to a hosted wordpress.org instance.  There might be hitches and problems as I get going with this.  As of today, you can see the old postings on health IT or healthcare IT under http://svfruitstand.com/healthit. I hope to add more posts to it soon.

I also have not abandoned commenting on what’s new in IT and trends in social media and software.  Those blogs have been migrated over to http://svfruitstand.com/swblog.

IBM and SPSS predictive of further analytics M&A?

It looks like the consolidation of analytics vendors are continuing – IBM announced the purchase of public company SPSS today for $1.2 billion, less than 2 years after they bought Cognos for $4.9 billion.

According to other responses on the article on techcrunch, there were a couple more mergers recently in Europe with AG buying IDS Sheer and SAP buying up SAF of Switzerland (blog entry in German) as well.

This may be an indication that big software companies realize analytics software is a great services cash cow that they can milk for consulting revenues. After all, analytics is one of these technologies that needs to be implemented for your particular business and your set of data to drive your business decision making.

I hope beyond service revenue, these mergers are also driven by a recognition that enterprises are moving beyond reporting and actually taking advantage of the predictive aspects of analytics.  If true, this will indeed help companies  transform into intelligent business. Do you see that starting to happen in your space?

Along the same line, I am reading a book Smart (Enough) Systems by James Taylor and Neil Raden and hope to have more to say about the predictive analytics space later.

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Business Intelligence or Intelligent Business

A recently blog by Josh Healan of DataForge said that many companies failed despite having invested heavily in expensive software (e.g. SAP). I think he correctly pointed out that software, including Business Intelligence applications, cannot tell the executives about future disasters if they choose to run their business intelligently.

There might be a few reasons why businesses fail to execute despite their heavy investment in SAP, Oracle or ‘put your vendor name here’.

  1. Data unavailable – The applications they bought were not designed to provide intelligence to help the executives make decisions.  They were merely designed to support individual transactions without considering the strategic goals.   Ask you vendor to provide the functionality or implement your own BI against it.
  2. Executives fail to grasp the importance – The business intelligence and analytic applications tell the executives that something is up, but the executives fail to understand how these data points impact their business.  There is no substitute for an intelligent leader.
  3. CPM treated as one time project – Corporate Performance Management is a process, whether it is implemented using Cognos, Hyperion, Business Objects or some other products.  If the executives do not revise the goals as things change and manage the business to the new goals, the software investment would be for naught.

Spending money on ERP, CRM or Business Intelligence applications does not automatically make an intelligent business.  In my days of managing a BI product for IT organizations, I often asked the customers what business decision or process they wanted to optimize.  If they did not know, no amount of BI investment would help them execute better.

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Driving Continual Improvement

A few weeks ago, I wrote an article titled Begin from the beginning – IT Continual Service Improvement on a company blog about IT Continual Service Improvement (CSI).  Even though it was in the context of ITIL v3 and IT organizations, I think the points I raised were generally applicable to any process management situation.

You need to  measure, set baseline, choose realistic goals, refine process, measure and check again.  It is an ongoing process.  Even if you have succeeded in meeting your service and quality goals, you need to apply this methodology to keep the process within control.  Entropy is always increasing.  If you stop watching it, it will veer away from your target, I guarantee.

A colleague, Meri Gruber, provided some great insight after I told her about my blog post – once you have sufficient data, you can even apply business rules and predictive analytics for what she termed as “next generation CSI”.  Anyone interested in attempting CSI TNG?