The new generation of iPad-enabled knowledge workers has little patience for the archaic user experiences (UX) offered by entrenched enterprise IT providers, whether on their PCs at work or on their smartphones on the road (or at their kid's soccer game). And many in enterprise IT, from software engineers to IT managers, are moaning the loss of control as elegant, easy-to-use consumer technologies like the iPad and Dropbox reshape expectations in the corporate landscape. For the big tech companies that used to dominate enterprise IT with their task-oriented utilitarian offerings, such as HP and RIM, the enterprise is no longer a safe haven for their product portfolios in the 2010s.
Behind the current wave of the "consumerization," there are actually signs of a reverse trend in which the world's most effective enterprise user experiences may reshape the future of all UX. This budding wave could benefit the enterprise IT industry tremendously — if they get it right.
The next wave of innovation will be driven by business-grade solutions that combine real-time analytics and improved UX to support better decision-making in a host of new areas. These innovations will range from how we manage large-scale infrastructure such as urban traffic, to how we manage our heating bills at home; from how we manage collaboration on a trading desk to how we prioritize our personal email inboxes.
And here's the twist: as the boundaries between work and personal lives blur, it often feels like our lives are getting more and more "disconnected." Information is funneled into more and more specialized applications to help us stay perpetually connected to our friends, colleagues, clients, and family (of course not always in that order). Apps have seeped into every crack and crevice of our personal and professional lives. So the mental involvement for managing these apps can get out of control. Even simple decisions, like where to meet for dinner, can involve multiple data streams and complex cross-channel and cross-app collaboration, from Yelp to OpenTable.
In our daily lives, we're facing logistical and decision-making challenges that were once confined to IT managers in large corporations. How can we bring all of these streams of information together in a more useful manner?
Many IT companies, from Facebook to GE, are exploring innovative ways to extract value from Big Data, or ever-growing collections of complex information, which we're all constantly supplying via our social networking streams and online purchases. The greatest opportunity is emerging from the ability to combine structured and unstructured data to improve decision-making and enhance our predictive abilities i.e. make smarter decisions. "More than the amount of data itself, the unstructured data from the Web and sensors (in our environment) is a much more salient feature of what is being called Big Data," according to Thomas Davenport, visiting professor of Data Analytics at Harvard and author of Competing on Analytics: The New Science of Winning.
For example, the goal may be to correlate brand discussions on Facebook and Twitter (unstructured data) with product sales for (structured data) to make the right recommendation to a consumer when they enter a store or look up a movie. Startups have already begun to emerge from the enterprise, like Rocketfuel, that harness industrial grade algorithms to better target product recommendations. Thanks to the profusion of cheap sensors in our cars and fridges, these data streams are moving out of our social networks and into our environments.
But we will only get so far when the ultimate source of value is individual consumer preference. Enterprise IT companies — IBM, GE, HP, versus dynamic startups beginning from scratch, may actually have the edge when it comes to extracting value from a host of different data streams. Why? Because they have simply built up the types of analytical experience and tools to do so.
Take, for instance, the comparative data collected from a popular app used on Facebook versus the data collected via a major Wall Street trading firm. Even with the increased amount of data being captured via consumer clicks each day, the conversion rate across many categories of online marketing remains in the single digits. In contrast, even a few percent point increase in productivity of a single Wall Street trader, can lead to millions in additional revenue per year. But the "user experience" layer will be critical in unlocking the value of data for consumers and businesses alike, as we have seen in our practices at General Electric and frog. And enterprises are starting to wake up to the value of UX in even the most specialized, industrial environments like wind farm management. Here are two real-world examples of challenges that draw from our recent experience working with large-scale enterprises that have broader potential to impact the consumer market:
1.Visualizing Communication Patterns: The financial services industry is saturated with structured market data. For many on Wall Street, the opportunities for competitive advantage have been reduced to betting on high volume, high speed infinitesimal market movements, such as small changes in the relative value of currencies. In this context there is new-found interest in the role that sentiment and opinion can play in influencing market behavior. Unstructured data from sources like Twitter are beginning to be taken seriously by the likes of Thomson Reuters and Bloomberg. What would happen if you combined this sort of broad sentiment analysis with CRM and portfolio data from your most valuable customers? What sort of social graph could you build? How could this new layer of information improve the performance of buyers and sellers, as they react to market events and communicate with one and other across institutional boundaries?
Wall Street is rapidly developing an overlay of data on communications and sentiment that is equal to the level of precision in their market tracking tools. Financial service IT companies, like frog client IPC, are in a unique position to develop next-generation, intelligent communication tools for traders around the world.
How could these same visual patterns, used to map the flow of information and influence in financial markets, apply to making sense of the personal data that people share via Foursquare or Yelp? Imagine if you could search through the contents of your priority communications, whether voice, text, email or tweets and correlate to a social media influence scoring service such as Klout or other measures of interest. Imagine if all of your various inboxes/call histories were tagged using a common visual scheme to denote key topics of interest with a social graph of "interest" generated in real-time. Google has already taken a step in this direction when they introduced the "important messages" filter in our Gmail inboxes, filed according to our response history. But this is just the tip of the iceberg. Today a buyer on Wall Street can correlate market moves across a broad array of software tools, all of which represent market data using a consistent language of color and behavior. But some day soon your personal call history will look more like a stock portfolio than a to-do list and we will wonder how we ever managed the daily avalanche of communications without this additional layer of intelligence.
2. Conversing with the Internet of Things: "Smart" devices like the Nest thermostat are slowly seeping into the consumer market, opening us up to new streams of data from sensors embedded in our physical environment. Some day soon this stream of information and updates will be seamlessly integrated into our overall communications, opening the door to much more rich and intelligent ways to interact with our homes or our cars. When you think about the role of these systems on a different scale, say at the urban level, these sorts of inputs can promise huge improvements in daily life by helping to optimizing vast flows of human activity related to commuting, health, and public safety.
To realize the promise of this sort of intelligent infrastructure, huge amounts of data need to be collected and analyzed on a real-time basis. Cities and resorts are starting to make some headway, thanks to support from IBM and others. But, once again, the enterprise is way ahead. Infrastructure companies like GE have been gathering real-time data on power plants, locomotives, and aircraft for years, thanks to a wide variety of sensors. Now these companies are looking for fresh ways to unlock this data and make it useful in the moment. GE calls this the "Industrial Internet" and believes that unlocking this information will bring dramatic productivity gains and entire new businesses to life.
A case in point is MyEngines, a GE mobile app that allows fleet managers to track the status of aircraft engines in the air and on the ground to better manage their fleets and plan and predict maintenance issues before they come up. Imagine 100s of multi-million dollar engines becoming your next circle of "friends" on Facebook. How would you use that data to look for historical patterns, identify abnormalities, predict issues, and make decisions in real time? What GE learns about these opportunities may set the model for how we monitor an elderly parent across the country or our HVAC while we are on vacation. In particular, we may see the emergence of a host of new OnStar like services that monitor these feeds, correlates them with a variety of relevant data sources and predictive analytics to help us to respond in an effective and timely manner.
These are not futuristic scenarios. Both are real world examples of enterprise technologies we have explored within our organizations, and with our clients and partners. These ideas represent a new frontier of innovation where the enterprise can re-capture the lead in successful UX strategy while creating a new wave of technologies with immense potential for social value. Such advances are enabled by the key drivers of the "big data" revolution — ubiquitous internet, on-demand cloud computing, and cheap, connected sensors — not to mention numerous machines (and robotics), from engines to healthcare equipment to wind turbines.
This is the next and best opportunity for Enterprise IT software makers. They better not screw it up. But to lead this revolution they must also adopt the latest advances in user experience design that have emerged from the consumer "app" marketplace. The key is not just better algorithms but more intelligent ways of surfacing the data in meaningful ways, through fresh visual and interaction paradigms. As user-experience practitioners, we see enormous opportunities in a coming wave of data organization tools, which will blend the best interface elements of personal devices and apps and "smarts" of enterprise software and hardware.