Five years ago the world-wide-web was horrified at the concept of usable user data. Today every business from high fashion to the local laundry-mat wants to know how to convert customers via predictive intelligence. Technology is gearing up to meet a Big Data conundrum, as marketers wring their hands awaiting the golden ring that signifies an R-O-I bonanza. But at this stage of trend analysis, most experts agree that the analytics ship has not yet arrived. Here’s a succinct look at where we really are.
IBM’s Watson is still in shadow for “wowing” businesses and onlookers – Courtesy Atomic Taco Via CC 2.0 License
What About IBM’s Watson?
Promises, promises, promises, we’ve all heard our share. From semantic search and artificial intelligence, to push button PR and marketing, the world of digital business has had its fair share of flops, and conversion charlatans too. One of the most promising (pun intended) analytics entities I ever saw, IBM’s Watson just fell on its intelligent face at CES recently. To add insult to its bloody-intelligent nose, the quizzical natural language project from the world’s most famous computing people just helped lose the company 17% share value in the last 12 months. Added to this under-achievement, the fact three executives retired has not done much to bolster confidence in Watson. IBM CEO Ginni Rometty’s keynote promise at CES, that computer technology will “change the way you are,” seems as far off as ever. The fact of AI and machines taking over our world is, we simply are not there yet. Despite clever and costly IBM marketing campaigns, Watson is still infantile. This is the cold reality.
The Efficacy of the Internet of Things
The Internet of Things (IoT) will soon be the largest single source of data on the planet, yet almost 90% of that data is never acted upon.” This is what, Harriet Green, General Manager of Watson IoT and Education had to say about this bold new Internet buzz paradigm. Excuse my sardonic tone here, but business people will soon need a Watson computer assistant to be able to filter the billions of buzz and marketing hype jargon bits into usable intelligence. The term IoT, first conjured into existence in 1989 by British entrepreneur Kevin Ashton in 1999, loosely described a futuristic inter-connectivity in between the physical devices digital communications is powered by, and real human connectivity and control. Morphed into a current hypothetical that powers up the imagination (and marketing firms), the IoT is a reality, but nowhere near the Matrix-like science-meets-fiction evangelists expound upon.
Even though Gartner, Inc. research predicted some 26 billion device connected to “us” will go active by 2020, communicating to those devices in a meaningful way is still far off. One major stumbling block is in fact the way marketers and media influence the IoT innovative process. In a very real sense, the IoT cannot come into existence because the people who want to target customer data and influence want it most! In short, the sales people of digital aim to process data. What is happening is a sort of refinement of the advertising model, or in hard terms an IoT transformed into a corporate propaganda machine. Business’ influence on the development of the Big Data processes ends up limiting the development of the innovation. The problem arises from the newfound trend toward trying to create so-called ambient intelligence or autonomous control. You see the original IoT concept did not even need the literal “internet.” This theory heads off into a deep analysis, but the influence of media and business on the new IoT, does have its negatives. And in this we see the new IoT is in itself, preventive of the shift to Big Data intelligence.
Overcoming the Insurmountable
Three years ago TechRepublic ran a story entitled; “How to overcome Big Data’s main stumbling block.” Back then the hurdle was in making Big Data pay dividends for companies large and small. The piece relies heavily on research from Matt Ariker, McKinsey & Company Chief Marketing & Sales Officer. His take on solving for Big Data X back then was, and is sound. Breaking it down, Ariker essentially narrows Big Data utilization down to; focus, building a roadmap, prioritization, and commitment.
Today we see Ariker’s imminently sound advice having been largely ignored by business. This report of his at the Harvard Business Review is telling. The “commitment” Ariker advises businesses ramping up their Big Data efforts to invest in in 2013, is still a huge problem in November 2015. Although the McKinsey COO does not come right out and say it, it’s clear in the research, that companies are not fully committed to what I would call “wholly integrated” data analytics.
“We’ve found that the enthusiasm to use marketing analytics often results in a “peanut butter” approach – companies spread it around everywhere. The result is a poor articulation of the goals of the use of marketing analytics, a lack of focus on what it takes to get it right, and limited application of learned lessons across the organization.”
Other language in the report sugar coats the fact CMOs are either not empowered, or in a sort of fledgling committal zone where their respective institutions are concerned. Across the gambit of industries, we see a very slow literal uptake, and as Ariker suggests, a bit of shot gun targeting.
Big Data in the Now
One good example of an industry steadfastly entrenched in often archaic systems; the hospitality niche still uses digital tools almost begrudgingly. Almost all the independent hoteliers I work with have just gotten over the shock of paying OTAs and other conversion channels. For them, TripAdvisor is still some magic box with mysterious workings, one they’d as soon abandon, but cannot. As for predictive analytics prowess is the hotel business, most hoteliers now understand that providing a killer guest experience depends on knowing all about the customer. However mighty the potential for utilizing mountains of world traveler data may be though, the reality of ROI from business intelligence for hotels has not arrived. There are many reasons for this, not the least of which is an inability to shift from sales people mulling over spreadsheets, to simplified business intelligence systems. Taking the steps to change can be painful, and there’s actually very few solutions on the horizon. One that’s made some waves lately, is the hotel analytics startup, SnapShot GmbH, here in Germany. I tracked down their CEO, former Google Germany Director, Dr. Stefan Tweraser (at right) in order to get his take on where this industry is adaptation wise. Here’s what he has to say:
“The hotel tech industry is ripe for revolution. Nothing much has changed in years, things that you take for granted in other industries simply do not exist here. And that’s why I’m here, to help hotels really access their data so they can focus more on the guest experience.”
Now that we’re back with our feet firmly on planet Earth, the possibilities are endless. To get a crystal ball look at what we can expect in the months and years to come, I contacted Woody Wade (at left), award winning author of “Scenario Planning: A Field Guide to the Future”, and author of the upcoming “Hotel Yearbook 2036”, a provocative look at how the hotel industry could develop two decades from now. I asked Woody about his vision for the future of big data analytics for hotels. His first reaction was to the point; “Imagine a hotel chain able to combine big data with facial recognition,” he suggested. To be sure, Wade’s vision of the hotel employees wearing some future version of Google Glass, a heads up display that allows staff to instantly recognize on guest in a chain’s millions of loyal customers, it is a tool completely within reach. But the former Executive Board member of the World Economic Forum takes this vision much further, Wade continued:
“Walk down the hall of this hotel, and the specs sitting on the nose of an employee walking the other way instantly check the guest’s face, IDs him against the guest register, and zaps a set of relevant facts to the employee via augmented reality, allowing the employee to not only greet the guest – but upsell him.”
In Wade’s future marketing fantasy our hotel guest in question happens to be a big spender from Brazil. Mr. Vargas, for the sake of argument, he’s maybe not even aware the hotel’s cigar lounge just opened. He’s certainly got no idea the barman there is an award winning mix-master. As Wade suggests, the possibility for adding value and revenue via guest and other data, it’s exciting and endless. But this brings us back to square one really.
A super computer brain, a massive intelligence, connected via the cloud, that connects human beings to real nuts and bolts technology, we’re headed there to be certain. However, the science fiction residual presence that empowers hyperbole from us PR and marketing people, it is sometimes counterproductive. Elevating expectations into the stratosphere, overselling that hotel owner who trusted, the disappointment costs and costs. Every time Big Data is oversold, and when the analytics cannot serve up that big ROI, the ecosystem that could develop is retarded a bit. Watson, as brilliant as that IBM intelligence is, has been hyped out of this world.
Now, since true walking AI is not yet perfected, even the most optimistic tech geeks (like me) get discouraged. The end result is, we’re harder to convince when Big Data finally does deliver. So the expectation has to be, as difficult as this is for me to say, moderation in all things. Don’t expect something out of a Gene Roddenberry vision just yet. It’s more realistic to let Big Data help your business improve in increments. And remember to prepare the roadmap with realistic goals in sight, prioritize to focus on those goals, and most importantly ensure your business is committed. You can build a customer tractor beam once expectations and goals coincide.
