Today, we got to hear from Aha! at the Boulder BI Brain Trust.
Once I disconnected my brain synopses that were connecting
the company name to the 1980’s song and innovative video “Take On Me”, I wrapped
into the ideas they were presenting.They are taking on the “magical, mystical, overloaded” term of
“analytics” - a market expected they expect to grow 10% next year.They are targeting the “93%” of business
users that don’t use analytics today.Aha! defines their space as the “Business Embedded Analytics to
operationalize predictive and other analytical models.”This 4-year-old company is part of the
growing trend of software-as-a-service providers.
After spending some time defining analytics, which remains
elusive, Aha!’s definition is “Analytics are models and model-based decision
making.”Companies can differentiate
themselves with the output of analytics.
They are attempting to bring, to pull a title of a talk I
used to give, “data mining to the masses.”This is a noble idea and has been pursued for quite a few years.Microsoft, for one, has made great strides
here.The idea relates to the concept of
“Attention economics”, which is
an approach to the management of information that treats human attention as a
scarce commodity, and applies economic theory to solve various information
management problems (from its Wikipedia entry.)
I have said this before, but it bears repeating here where
Aha’s form of analytics is like the “data mining” definition we have used and
they are addressing these problems with data mining.
“Data mining has long been a means
to attaining high business value from a warehouse.As the means of automating discovery to
explore and identify new business insight, it stands alone as an access
method.Interactive Query or OLAP
presents the measures of the business organized around their logical
dimensions.Hierarchies in the
dimensions allow for organized grouping and lead to drilling up and down in the
data to find what you’re looking for.Mining, however, makes you aware of situations that may represent new
market opportunities or business problems that have yet to surface to the level
of notice through standard interaction methods.
However, much of data mining has been
relegated to the domain of a special breed of expert, often holding a Ph.D. in
a statistics discipline.The mining
process currently deployed in many organizations is not only time consuming due
to the challenge of the tools and the semantic gap between the front line and
the statisticians, it is also non-iterative in nature.Discovered nuggets flow from the miners to
the front line and are only selectively interesting and actionable.The feedback loop is missing.It’s like having a luxury car but keeping it
parked in the garage at all times.Mining tools that are interactive, visual, understandable,
well-performing and work directly on the data warehouse/mart of the
organization could be used by front line workers for immediate and lasting
business benefit.
The advanced techniques deployed in
a lot of mining programs are generally well beyond the understanding of the
average business analyst or knowledge worker.If this advanced level of analysis is reserved for the few, instead of
the masses, the full enablement of the warehouse in the organization cannot be
realized.If those whose analytical
interests stay well within the complexity of computing sales commissions are
shut out of mining, mining is not nearly as effective as it could be.”
Cut to Aha!’s take on this problem… via a long-awaited demo…
In the healthcare example, they created a large flat file
pulled out of the client’s databases, to assess propensity to disenroll.In the example, they delivered improved
retention rates at a measurable NPV of $43 million.
Customers of Aha! (product: Axel) are able to interact with
a model until it is perfected.The model
runs on continual updates of data sent to Aha!.Overall, including some things seen under NDA, it’s impressive.Some of the challenges include that the
collaboration is occurring only while the customer is reviewing the output,
though the metrics are numerous and interesting and the interface obscures some
of the value.
Aha! is bringing together an old world that needs change -
data mining/predictive analytics - and the new world of software-as-a-service.
