Archive for October 2015

IBM Buys The Weather Company. Why?

This past week IBM announced that it was going to pay over $2B for the digital assets of The Weather Company. That means everything but the TV channel because who buys into the last millennium media when you can have something relevant? I am surprised how little buzz there is about this deal. It’s not like IBM didn’t promote it. The news was the lead keynote on Wednesday at IBM’s Insight conference and there was the usual press and analyst blitz. It’s not like they were trying to hide it.

My assumption is that the real impact of this acquisition hasn’t sunk in yet. It also doesn’t help that IBM is masking the real and incredible value this acquisition has for IBM by talking mostly about the Internet of Things and analytics. It’s true that these assets will have a major impact on the type of analysis a business can perform. IBM is correct that weather affects many types of business decisions. They are also acquiring some interesting ad placement and data gathering technology. None of that is worth what they paid for The Weather Company’s digital business or that couldn’t have been obtained in a different manner such as licensing.

The real impact will be the emergence of IBM as data merchants who can deliver valuable streams of unique data, along with the tools to analyze it, as a compute solution. The agreements with Twitter and Box all point in this direction. Twitter is a rich trove of streaming social media data and Box allows IBM to tap into unstructured corporate data. While they won’t be reselling the latter, they will be enhancing it with other data they sell and analyzing it as part of a solution. I wouldn’t be surprised to hear about IBM licensing or acquiring other types of textual and numerical data streams such as demographics, stock data, legal references, or scientific journals in the near future.

What IBM can do that few other companies can do is sell vertical industry solutions that combine their own and licensed data with customer data and the tools to process and analyze it. Let’s say there is an oil company deciding where to dig a new well. IBM has the capacity to help craft a selection analysis solution that looks at the weather related costs for drilling and maintaining a facility, social media signals that show political resistance to the well, and geo-spatial information combined with company geological surveys – all filtered through a cognitive computing lens – that helps find the best site for the project. It’s hard to find any other company that can provide a package that includes so many important elements for this type of analysis.

IBM’s acquisition of The Weather Company’s digital assets signals a recognition of the importance that contextual data has to technology solutions delivery. In a way, it’s the ancient computer science argument about garbage in-garbage out. With this acquisition, IBM is helping to insure less garbage going into critical analysis. More so, it is a recognition of the value of data in of itself. Technology can be had from a number of companies including IBM. Data is like a beautiful, precious gem – something unique, rare, and valuable that enhances everything around it.

IBM Watson Analytics – Analytics for All

I had the privilege to attend the IBM Watson Analytics “Analytics for All: Empowering Everyone to Know ” event on October 14th. I like these events better than the massive conferences. They are more intimate and allow for more meaningful conversations. It also afforded me the opportunity to reach a single day personal best of 11.1K impressions on Twitter. There were the company executive presentations and customer panels that have become common at all types of tech events. Often these presentations feel a bit fractured as different speakers cover a range of topics. This was not the case at the IBM Analytics for All event. Clear themes emerged from both IBM and its Watson Analytics customers. These themes are valid for all analytics software.

  • Empowerment for the business user. Everyone admits there is a deficit of data scientists while business users yearn for more analysis to help make decisions. IBM Watson Analytics puts tools in the hands of the business user in order to make it easy to analyze data. There is a caveat: when we say “business user” we really mean a business analyst as opposed to a data analyst. It’s unlikely that executives or managers would spend much time using any analytics tools when they have others to do this. They are much more likely to consumer analysis from a business analyst who uses IBM Watson Analytics. IBM is correct that some managers will probably use IBM Watson to prototype what they want or develop some ideas about data. As IBM says, IBM Watson Analytics is an accelerator. Still, it will reduce the need to wait on a handful of data scientists who would rather be developing complex models rather than running reports for managers.
  • Time is a factor. It’s not just getting the analysis, it’s how fast you get it. A lot of decisions need some immediate data and can’t wait for someone to develop a query or report. Because many conventional tools are tough to use, it holds up getting important analysis even from business analysts backed by data scientists.
  • Design matters. IBM Watson Analytics shows how design affects software. The customers on the panels said it over and over – the design helped non-technical people to analyze data without getting bogged down in the software.
  • Analytics needs to support diverse business needs. Many of the customers said that they had to support different types and sizes of teams. The sheer diversity of business users screams out for tools that are easy and adaptable. It was one of the reasons that the customers were really into self-service. There were just too many types of data and analysis.

The new features announced by IBM at the event reflect these themes. The forthcoming Expert Storybooks will allow data, analysis, and even extensions to IBM Watson Analytics to be packaged by third parties for use by others. An Expert Storybook user will then be able to perform analysis and use data that they would be incapable of obtaining on their own without a consulting engagement. It also allows a new market for purveyors of data and analysis. Additional design enhancements are, as IBM put is “in the labs.” These include a unified analytics capability that makes it easier to access different parts of the workflow from anywhere else in the workflow. Ultimately, this changes the linear data analytics workflow into a more fluid process.

A truly killer feature, currently in development, is the ability to identify patterns in existing data and apply it to new or different data. This is the type of feature that is truly a time saver for anyone doing serious analysis. Another future feature, the ability to derive a model for a time-based forecast from a data series is one of those helpful shortcuts that saves having to build this type of model. These new features all combine the ease of use and time savings that business users want to see applied to the process of analytics.

The market for business user analytics tools is still new. Most focus on visualizations with minimal data manipulation or modeling. By leveraging the cognitive power of Watson, IBM Watson Analytics is pushing the advanced features usually reserved for data scientists downstream closer to those who make use of the analysis.