The Big Thoughts from IBM Think

    I’m at IBM Think and there sure are a lot of people here with me. This event comes coincidentally in a week when IBM’s oldest consistent competitor, Oracle, missed its earnings expectations. IBM is one of a very short list of companies that has been around for over a century and still does massive amounts of unique research. This means that some really interesting and unique ideas come out of this company. Where other firms mostly focus on pitching products, IBM continues to stand out by pitching concepts. These concepts are based on a combination of IBM’s history and unique internal research efforts. I honestly think that if more firms in tech did the kind of research that IBM does, the more strategic they would be, and the higher the likelihood that they’d survive the decade, let alone the century.

    Let’s chat about some of the big thoughts I picked up out of the show this year.

    Data Is the Basis for Competitive Advantage

    According to IBM, only 20 percent of the data is online, which means that 80 percent of the information needed to advance our firms, cure diseases, prevent the next war, or assure the next political leader can (and wants to) actually do the job isn’t currently accessible.

    IBM argues that one of the big competitive advantages is with firms that have this critical data about their customers, products, industry trends, and environmental changes and can form decisions based on this data.

    The age of executives largely making decisions from their own gut is ending. Firms that can change their practices to make decisions data driven will, as these practices shift, quickly overcome those that do not.

    Process Needs to Include Learning

    I was just reading an article that seemed to argue that training was unimportant because not only were millennials moving between jobs a lot, but all age groups were changing jobs at a massive rate. The author wasn’t really pushing a lack of training but pointing out that even more training was necessary, and the point was that if you want to cut costs, then a far greater focus on retention is critical.

    I agree with the last, but people will always move and the time to do focused training just never seems to materialize. Employees are, and will continue to be, expected to hit the game running. This isn’t a new thing. When I first came to work for a firm that later became part of IBM myself, I was two weeks in thinking I was going to be fired because I still had no idea what I was supposed to do. I don’t wish that experience on anyone.

    IBM at Think argued that training needs to be embedded in every process so that a new employee could start and self-train on the job. You may start the job not having a clue like I did, but you are also given the ability to self-train so that you aren’t as concerned that you’ll not last the month.

    The Need to Eliminate Bias

    Of five presentations from IBM Labs, two stood out to me. One spoke to the increasing death of plankton, which produces two-thirds of the world’s oxygen. The cause is pollution, which isn’t just causing global warming. I’ve found that it is really hard to be successful if you are dead and the loss of oxygen would clearly have an unfortunate result. But the bigger issue, and one related to this problem, is research bias. Much of the research that is done is intentionally biased; the researchers are missioned to provide a predetermined outcome. But worse, a lot of the research that is intended to be unbiased is biased accidentally by preconceived notions of the researchers, biased samples, or mistakes in analysis. IBM is putting a substantial effort into the critical identification and elimination of bias. I believe this isn’t just critical for good business but for the world’s survival.

    Wrapping Up: The Watson Assistant – Or a Smart Siri

    If you tie all of this together, turning most all your data into information you can take action on and found future decisions, assuring how to do a process is embedded with the process, and eliminating bias, the concept of a super-smart digital assistant comes to mind. I’ve often wondered why Apple’s partnership with IBM didn’t result in a smarter Siri, given that Apple’s digital assistant is currently the dumbest. Well, IBM is stepping into the breach with the Watson Assistant, a pre-trained version of Watson that potentially could address all three concepts. It could help executives (and service providers) make better decisions, it could provide new employees with the embedded knowledge required to operate their job-related processes, and it could provide unbiased answers to critical questions. I’m now wondering how long it will be before other firms realize that if they want to compete with Amazon’s Echo, rather than licensing Alexa, they should instead license the Watson Assistant.

    In the end, IBM Think got me to think, and that is likely one of the big reasons to come to this show.

    Rob Enderle is President and Principal Analyst of the Enderle Group, a forward-looking emerging technology advisory firm.  With over 30 years’ experience in emerging technologies, he has provided regional and global companies with guidance in how to better target customer needs; create new business opportunities; anticipate technology changes; select vendors and products; and present their products in the best possible light. Rob covers the technology industry broadly. Before founding the Enderle Group, Rob was the Senior Research Fellow for Forrester Research and the Giga Information Group, and held senior positions at IBM and ROLM. Follow Rob on Twitter @enderle, on Facebook and on Google+

    Rob Enderle
    Rob Enderle
    As President and Principal Analyst of the Enderle Group, Rob provides regional and global companies with guidance in how to create credible dialogue with the market, target customer needs, create new business opportunities, anticipate technology changes, select vendors and products, and practice zero dollar marketing. For over 20 years Rob has worked for and with companies like Microsoft, HP, IBM, Dell, Toshiba, Gateway, Sony, USAA, Texas Instruments, AMD, Intel, Credit Suisse First Boston, ROLM, and Siemens.
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