Executives with a capital “C” in their title generally don’t have a clue on how to adjust to the social, mobile, and cloud-based business world. Now IBM wants to help these Luddite execs adapt — by plunking them down into a new lab where it will show them what the IT tools at their disposal can actually accomplish.
IBM’s new Customer Experience Lab aims to deploy 100 hand-picked specialists — industry titans from the world of machine learning, analytics, and a slew of other “Big Data” fields — as a consulting consortium aimed at aiding C-suite executives.
“Take for example a CMO whose life has changed quite a bit as a result of social and mobile in the last couple years,” explains Clay Williams, senior manager of “front-office innovation” at IBM. “The goal here is to bring the headlights that IBM research has to shine and show them further down the road… so that IBM can help them chart the path forward.”
In other words, IBM wants to provide some tools, and some advice, to help top executives learn how not to screw things up in a landscape they have no hope of understanding on their own. After all, a CFO may be well-versed in the complexities of financial-based business models, but isn’t going to have the slightest idea of how to employ data mining and machine learning to better understand a single customers needs.
IBM knows that, and it insists it isn’t looking to educate these individuals. “It’s not so much teaching, but delivering these new technologies,” Williams says. “It’s built around us working in partnership.”
“Big Data” Tools
With more than $6 billion going into research and development each year, IBM is one of the very few global companies capable of offering up an expensive, need-based Big Data consulting service.
But what exactly will it look like? Well, the new IBM lab aims to give business leaders the opportunity to work alongside those 100 experts in order to jointly create new business strategies based on what the companies’ own data tell them.
For interested companies, IBM will pinpoint a C-level candidate exec and help craft new business strategies for him or her. Or, if you prefer the original IBMspeak: “From nomination to partnering to understanding the client problem and finding the right research team, then what we do is look at proof of concept model,” Williams says. “We see if they are appealing, rapidly prototype some of those ideas and then go to a full solution process.”
IBM outlines three generic sorts of breakthroughs it has identified for potential clients to leverage:
- Customer insight: Applying advanced capabilities such as machine learning and visual analytics to predict differences in individual customer behavior across multiple channels.
- Customer engagement: Using deep customer engagement to drive insight and continuously deliver value by personalizing engagement, versus transactional experiences.
- Employee engagement: Embedding semantic, collaborative, and multimedia technologies to foster employee engagement and insight – in person and online.
Mobile Banking? Great, But What’s Next?
Williams offers an example from banking, both because that’s an area where Big Data technologies can be particularly helpful, and because it’s the sector in which two of the IBM lab’s first clients — British mutual institution Nationwide Building Society and Mexican superbank Banorte — happen to operate.
“If you think about phase 1 of enabling [mobile] devices for banking, it was largely about parity with web-based banking,” he says — for instance, offering the ability to transfer funds or pay bills via mobile apps. Williams says IBM aims to go beyond that. If a bank wants to develop a plan for individual, social network-based experiences down the line, IBM can bring in a machine learning expert to parse how customers are interacting with businesses across various channels and develop algorithms for predicting behavior. “Now they’re are asking the deeper question: ‘What’s going to happen next?'”
And that’s the question IBM’s customer-experience lab wants its would-be clients to be asking. It’s supposedly the key with which international-scale business can craft strategies that fit the needs of individual customers — though exactly how you get there from here still remains a bit fuzzy. One thing is for sure: IBM is convinced that it depends on crunching mounds of data. Oh, and on paying those consulting fees.