I don’t know if my heart can take this much excitement. Yesterday morning, on July 29, 2015, I attended a very compelling presentation and demo of IBM’s Watson technology. (This AI-driven platform has been previously covered in these five Subway Fold posts.) Just the night before, I saw I saw a demo of some ultra-cool new augmented reality systems.
These experiences combined to make me think of the evocative line from Supernaut by Black Sabbath with Ozzie belting out “I’ve seen the future and I’ve left it behind”. (Incidentally, this prehistoric metal classic also has, IMHO, one of the most infectious guitar riffs with near warp speed shredding ever recorded.)
Yesterday’s demo of Watson Analytics, one key component among several on the platform, was held at IBM’s office in the heart of midtown Manhattan at 590 Madison Avenue and 57th Street. The company very graciously put this on for free. All three IBM employees who spoke were outstanding in their mastery of the technology, enthusiasm for its capabilities, and informative Q&A interactions with the audience. Massive kudos to everyone involved at the company in making this happen. Thanks, too, for all of attendees who asked such excellent questions.
Here is my summary of the event:
Part 1: What is Watson Analytics?
The first two speakers began with a fundamental truth about all organizations today: They have significant quantities of data that are driving all operations. However, a bottleneck often occurs when business users understand this but do not have the technical skills to fully leverage it while, correspondingly, IT workers do not always understand the business context of the data. As a result, business users have avenues they can explore but not the best or most timely means to do so.
This is where Watson can be introduced because it can make these business users self-sufficient with an accessible, extensible and easier to use analytics platform. It is, as one the speakers said “self-service analytics in the cloud”. Thus, Watson’s constituents can be seen as follows:
- “What” is how to discover and define business problems.
- “Why” is to understand the existence and nature of these problems.
- “How” is to share this process in order to affect change.
However, Watson is specifically not intended to be a replacement for IT in any way.
Also, one of Watson’s key capabilities is enabling users to pursue their questions by using a natural language dialog. This involves querying Watson with questions posed in ordinary spoken terms.
Part 2: A Real World Demo Using Airline Customer Data
Taken directly from the world of commerce, the IBM speakers presented a demo of Watson Analytics’ capabilities by using a hypothetical situation in the airline industry. This involved a business analyst in the marketing department for an airline who was given a compilation of market data prepared by a third-party vendor. The business analyst was then assigned by his manager with researching and planning how to reduce customer churn.
Next, by enlisting Watson Analytics for this project, the two central issues became how the data could be:
- Better understand, leveraged and applied to increase customers’ positive opinions while simultaneously decreasing the defections to the airline’s competitors.
- Comprehensively modeled in order to understand the elements of the customer base’s satisfaction, or lack thereof, with the airline’s services.
The speakers then put Watson Analytics through its paces up on large screens for the audience to observe and ask questions. The goal of this was to demonstrate how the business analyst could query Watson Analytics and, in turn, the system would provide alternative paths to explore the data in search of viable solutions.
Included among the variables that were dexterously tested and spun into enlightening interactive visualizations were:
- Satisfaction levels by other peer airlines and the hypothetical Watson customer airline
- Why customers are, and are not, satisfied with their travel experience
- Airline “status” segments such as “platinum” level flyers who pay a premium for additional select services
- Types of travel including for business and vacation
- Other customer demographic points
This results of this exercise as they appeared onscreen showed how Watson could, with its unique architecture and tool set:
- Generate “guided suggestions” using natural language dialogs
- Identify and test all manner of connections among the population of data
- Use predictive analytics to make business forecasts¹
- Calculate a “data quality score” to assess the quality of the data upon which business decisions are based
- Map out a wide variety of data dashboards and reports to view and continually test the data in an effort to “tell a story”
- Integrate an extensible set of analytical and graphics tools to sift through large data sets from relevant Twitter streams²
Part 3: The Development Roadmap
The third and final IBM speaker outlined the following paths for Watson Analytics that are currently in beta stage development:
- User engagement developers are working on an updated visual engine, increased connectivity and capabilities for mobile devices, and social media commentary.
- Collaboration developers are working on accommodating work groups and administrators, and dashboards that can be filtered and distributed.
- Data connector developers are working on new data linkages, improving the quality and shape of connections, and increasing the degrees of confidence in predictions. For example, a connection to weather data is underway that would be very helpful to the airline (among other industries), in the above hypothetical.
- New analytics developers are working on new functionality for business forecasting, time series analyses, optimization, and social media analytics.
Everyone in the audience, judging by the numerous informal conversations that quickly formed in the follow-up networking session, left with much to consider about the potential applications of this technology.
1. Please see these six Subway Fold posts covering predictive analytics in other markets.
2. Please see these ten Subway Fold posts for a variety of other applications of Twitter analytics.