Data Disruption – #TheDataWontFixItself

datadisruption
Data Disruption – #TheDataWontFixItself

Last week Informatica held its annual user conference InformaticaWorld 2016 here in San Francisco. The conference was about data powering business outcomes, and as part of the event, we held our first ever Data Disruption Summit, bringing together thought leaders to talk about architecting businesses to deal with digital disruption around us.  If you missed it, don’t worry. Over the coming weeks, Myles Suer (@MylesSuer) and I will blog on some of the major insights from the conference.

During the proceedings I caught up with Gwen Thomas, Corporate Data Advocate at the private sector arm of the World Bank Group, and founder of The Data Governance Institute. She made two very profound statements:

  • The data won’t fix itself
  • You cannot fix a problem at the level it was created (paraphrasing the Einstein quote).

Building your digital strategy

To put this into context, Jeanne Ross, Research Director and Principal Research Scientist at MIT/ CSIR (the Center for Information Systems Research), spoke about the need for businesses to re-architect (perhaps a few are very new and won’t need the “re-architect bit”) themselves. She offered that digital strategy basics are essentially about having a strong operational backbone in place – the table stakes – upon which you can layer a Digital Backbone of emerging capabilities. Then you need to pick one of the two other elements – Customer Engagement or Digitized Solutions – to bring focus to your digital strategy. See diagram below.

 

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A retailer like Nordstrom could be an example of the customer engagement strategy, while Apple might be an example of the digitized solutions side.  Jeanne suggests that you can only pick one because it will actually lead the other – i.e. if you pick Customer Engagement then the Digitized Solutions will follow to match what your customer wants. An example of starting from the other side is Apple, which followed Henry Ford’s mantra of not asking the people what they want (“people would have asked for faster horses”), but rather built the musicplayingtelephonecameraPC for a public that was intent on asking for the smallest possible cellphone. Who knew?

Efficiency versus Agility

Jeanne suggested that the pre-digital economy was architected for efficiency, while the digital economy demands agility. While an organization’s Operational Backbone supported (and continues to support) that aspect, organizations also need a Digital Services Backbone to deliver speed and agility (not just the ability to quickly add a service, but to quickly remove it if the service does not work).

Back to Gwen’s statements. It goes without saying that most organizations’ data is in a pretty big mess – in silos, diverse formats, latencies, technologies. The question then is how and where to fix it. Gwen suggested that continuing to capture our business data rules into our applications will not fix the problems and certainly will not get you to the agility you need.

Pathway to a solution

Gwen was very clear that the solution is in separating data management from the application logic, although trucking in another huge, inflexible platform is not the answer. Instead, her thinking is that the componentized platform approach would be a better strategy. Over the past two years, Informatica has built out their modular data management platform – Informatica’s Intelligent Data Platform (IDP) – that fits the description from Gwen.

  1. Many of the data activities and integration needed by an organization’s Operational Backbone can be done with Informatica tools like PowerCenter, Data Quality, and MDM.
  2. The recent innovations on the platform to support big data, cloud, NonSQL, self-service data prep, and data streaming means you now can add the components you need for your new digital services backbone. You use the same skills, reuse some of the work, and even some of the existing technologies!
  3. The platform aspects of the IDP with intelligent metadata and operational management across all of your data landscape – old and new – means you have governance, lineage and transparency at the ready – in a data layer that can be maintained separately from your applications.

Parting thoughts

Informatica announced its vision for the Intelligent Data Platform two years ago and has been building towards delivering the products to support this. With the most recent release of the Informatica suite, we are delivering most of the missing pieces. You can also view the video of Amit Walia, EVP and Chief Product Officer here.