Many of us have spent the past 10 years focusing on business intelligence solutions in order to help our businesses make better fact-based decisions. In fact, BI has been among CIOs’ top 10 priorities for more than a decade. These solutions have, for the most part, been successful — and we continue to improve our BI capabilities as the demand for fact-based decision-making goes deeper, wider, and further into the business.
This whole time, we’ve also been aware of the significant amount of unstructured data that resides within our business, and the fact that we struggle to use it to make better decisions. To begin to get value from this data, we have made our organizations more collaborative and implemented tools and platforms to support that collaboration — with varying degrees of success.
The fact remains that there’s a huge amount of unstructured information and data that we do not get value from. However, a growing number of solutions are beginning to mine elements of this data: product information, software code, legal case files, medical literature, messaging data, and other unstructured business data.
I’ve recently been working with TrustSphere, which is a messaging intelligence provider. TrustSphere has an interesting solution that mines your messaging data to get real insights and information from the mountains of emails and messages that bounce into, out of, and around your organization every day. This is an interesting concept, and TrustSphere has developed a number of use cases for its solution. I’ll be presenting at a webinar hosted by TrustSphere on February 25— feel free to register here.
IBM has just announced that one of Australia’s “big four” banks, the ANZ, will adopt the IBM Watson technology in their wealth management division for customer service and engagement. Australia has always been an early adopter of new technologies but I’d also like to think that we’re a little smarter and savvier than your average geek back in high school in 1982.
IBM’s Watson announcement is significant, not necessarily because of the sophistication of the Watson technology, but because of IBM's ability to successfully market the Watson concept.
To take us all back a little, the term ‘cognitive computing’ emerged in response to the failings of what was once termed ‘artificial intelligence’. Though the underlying concepts have been around for 50 years or more, AI remains a niche and specialist market with limited applications and a significant trail of failed or aborted projects. That’s not to say that we haven’t seen some sophisticated algorithmic based systems evolve. There’s already a good portfolio of large scale, deep analytic systems developed in the areas of fraud, risk, forensics, medicine, physics and more.
At a CIO roundtable that Forrester held recently in Sydney, I presented one of my favourite slides (originally seen in a deck from my colleague Ted Schadler) about what has happened r.e. technology since January 2007 (a little over five years ago). The slide goes like this:
Source: Forrester Research, 2012
This makes me wonder: what the next five years will hold for us? Forecasts tend to be made assuming most things remain the same – and I bet in 2007 few people saw all of these changes coming… What unforeseen changes might we see?
Will the whole concept of the enterprise disappear as barriers to entry disappear across many market segments?
Will the next generation reject the “public persona” that is typical in the Facebook generation and perhaps return to “traditional values”?
How will markets respond to the aging consumer in nearly every economy?
How will environmental concerns play out in consumer and business technology purchases and deployments?
How will the changing face of cities change consumer behaviors and demands?
Will artificial intelligence (AI) technologies and capabilities completely redefine business?
At IBM's Smarter Analytics event this week, clients and partners presented success stories about how organizations are driving business value out of big data, analytics, and IBM Watson technology.
- City of Dublin, Ireland using thousands of data points from local transportation and traffic signals to optimize public transit and deliver information to riders.
- Seton Healthcare mining through vast amounts of unstructured data captured in notes and dictation to get a more complete view of patients. Seton currently uses this information to construct programs that target treatments to the right patients with a goal of minimizing hospitalizations in the way that most efficiently optimizes costs with benefits. The ability to mine unstructured data gives a much more complete view of patients, including factors such as their support system, their ability to have transportation to and from appointments, and whether or not they have a primary care physician.
- WellPoint using Watson technology to improve real-time decision-making by mining through millions of pages of medical information while doctors and nurses are face-to-face with patients.
But, clients warned that as much as the technology is advancing, the biggest hurdles remained the internal ones. Clients stressed that they face a critical challenge in introducing, driving, and changing the organizational mindset to work in a new way that can take advantage of these great advances in technology. What did they suggest?
1) Executive sponsorship from the top (C-level)
2) Hiring or retraining for new roles like data scientists (schools like Syracuse are introducing and promoting new programs out of their iSchool, which can help with reskilling experienced talent from other areas)
OK, it’s time to stretch the 2012 writing muscles, and what better way to do it than with the time honored “retrospective” format. But rather than try and itemize all the news and come up with a list of maybe a dozen or more interesting things, I decided instead to pick the best and the worst – events and developments that show the amazing range of the technology business, its potentials and its daily frustrations. So, drum roll, please. My personal nomination for the best and worst of the year (along with a special extra bonus category) are:
The Best – IBM Watson stomps the world’s best human players in Jeopardy. In early 2011, IBM put its latest deep computing project, Watson, up against some of the best players in the world in a game of Jeopardy. Watson, consisting of hundreds of IBM Power CPUs, gazillions of bytes of memory and storage, and arguably the most sophisticated rules engine and natural language recognition capability ever developed, won hands down. If you haven’t seen the videos of this event, you should – seeing the IBM system fluidly answer very tricky questions is amazing. There is no sense that it is parsing the question and then sorting through 200 – 300 million pages of data per second in the background as it assembles its answers. This is truly the computer industry at its best. IBM lived up to its brand image as the oldest and strongest technology company and showed us a potential for integrating computers into untapped new potential solutions. Since the Jeopardy event, IBM has been working on commercializing Watson with an eye toward delivering domain-specific expert advisors. I recently listened to a presentation by a doctor participating in the trials of a Watson medical assistant, and the results were startling in terms of the potential to assist medical professionals in diagnostic procedures.