Big Data, Intelligence and Multi-Faceted Innovation

December 1, 2011
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I’m using this diagram (below) in two posts – this one, and one to be published shortly. Why? The impact of what this diagram is communicating is BIG, and affects many aspects of enterprises that want to innovate, to be competitive, to grow, to stick around for a long while. So it deserves the extra exposure.

 

I’m using this diagram (below) in two posts – this one, and one to be published shortly. Why? The impact of what this diagram is communicating is BIG, and affects many aspects of enterprises that want to innovate, to be competitive, to grow, to stick around for a long while. So it deserves the extra exposure.

While the use case for this example of multi-faceted innovation is Consumer Products industry, all industries have a stake here, especially as more and more technology offerings are becoming “consumerized”, and as cloud services and mobile usage for business grow. Multi-faceted innovation has great potential to transform enterprises into agile social businesses.

 Multi-faceted innovation 2

    

More teams in enterprises need access to more data, information, content, and many kinds of analytics to better perform their functions, to find more ways for the business to deliver what customers want, to be more competitive, more responsive in volatile economic times and in dynamic markets. Reliable, relevant information delivered at the right time impacts how strategies and goals are realized, how innovative a company can be, or even how long a company will be around. Information does no good if it languishes in silos, whether in the cloud or behind the firewall. Sophisticated and business-oriented technologies are needed to process information from diverse distributed sources, to analyze it, and then share the results for further refinement or even disputation.

The enterprise that has truly implemented multi-faceted innovation in as many aspects of its business as is appropriate is more likely to understand how important it is to tap into as many information assets as possible, whether they are ‘owned’ by the enterprise or sitting in cloud repositories for social sites. Information-driven insights are a significant aspect of multi-faceted innovation in the enterprise.

 

 

Business and InformationTechnology

Early in October I had the opportunity to attend an event sponsored by the Teradata Partners User Group (TDPUG). Teradata Corp. is a global vendor of software solutions for data management and governance, data warehouse capabilities, and for a wide array of analytics offerings. Obviously user group presentations usually show the positives of using vendor offering. But beyond that, the presenters usually talk fairly honestly about how they accomplished work for their companies that made a difference. The presenters are usually the hands-on people who know the ins and outs of their projects, as well as the impact on the business.

Part of my focus at the TDPUG conference – or Partners, as many call it – was attending business-oriented sessions (rather than technical deep dives) that might help with the following: 

“Big Data’ is a major topic for Teradata, and for recent acquisition Aster Data (‘big data’ analytics).  So I wanted to see how end users are able to connect highly varied and frequently complex Data to business outcomes that matter and to innovation.

Looking at processes working with data and analytics: are enterprises combining Business, Technology, Analytical, Creative, Collaborative activities to lead to good results for the business? If yes, how are they doing this? 

New directions for Teradata: how is the company changing from promoting its offerings mostly to very tech infrastructure-oriented target markets to adding strategic focus on the impacts of BI and analytics on business goals and needs – and how is Teradata connecting to roles related to the purpose of the business itself?

From the user presentations and those from Teradata: what kinds of roles are emerging, in biz and tech, that will make a difference for enterprises when it comes to data / information and analytics? 


    A Case in Point: Strategy, Innovation and ‘Big Data’

    A few sessions showed how to connect a strategic competitive intelligence core to analytical processes. A session with Vodafone (España) revealed a model for deriving real value from ‘big data’ that feeds into processes for competitive strategies that lead to innovating consumer products and business outcomesInstead of falling into the trap of “battling” competitors in feature-function wars, Vodafone shows that companies should be on top of what their current and desired customers want and need.  Otherwise, the risk is falling hopelessly behind customer expectations for new and important changes in the market and products that address this market.

    Vodafone bills itself as ‘customer-obsessed’ and in the highly competitive mobile phone business the company has to be. The strategic Competitive Intelligence (CI) group at Vodafone works with continuous analytical processes to feed intelligence into differentiation and competitive edge – from the customer perspective. Vodafone sees a lot of opportunity in understanding distinct customer segments and from quickly providing what each segment wants and needs. Many Vodafone target markets are highly volatile, so daily data updates and analyses are de rigueur to derive “next best actions” for Vodafone to take. Decision-making results from a convergence of analytics and intelligence in key areas: sales, marketing, competitive landscape – but revolving around deeply understanding each customer segment. This Vodafone CI approach illustrates the great payoff when business data silos are eliminated to achieve real integrated intelligence, leading to effective product and business innovation.

    The Vodafone session also epitomizes many of the Partners stories: when considering ‘big data’ analytic processes, the focus is not just the data itself, but what it’s used for. The data must be reliable, timely, right sources and integrations. Vodafone ‘big data’ analysis means many sources, high volume, fast intelligence leading to fast actions, and a daily reiteration of it all. Complex EDW and analytics infrastructure are aligned to business strategy and important outcomes, with a twist: the game changes constantly.

    An additional layer is the continuous re-analysis of methodologies for competitive and market intelligence processes, and of the validity of selected data sources, as well as context and the inclusion of new factors. To keep the intelligence efforts relevant, the dance steps are: change, iterate, stay agile (while knowing their competitors are likely taking similar actions as happens in highly commoditized markets).

    What Vodafone is accomplishing with its market and competitive intelligence core is a move to derive from an “unexpected” and innovative use of analytics the sorts of offerings that should be made available to target customers.  A new perspective on what should be the significant issues for target customers is essential to capture customer interest.  Competitive and market intelligence can also be leveraged to ensure that the customer’s perspective is maintained as a “reality check”. It’s an ongoing sense of the impact of what could be uncovered, the ramifications of what even the smallest pieces of information could mean for the company.  It ensures that business decisions and product direction are market-driven, reality-based, and actionable.

      

    Information Technology Underpins Multi-faceted Innovation

    When people think about what Teradata offers, most think of a very intense technology infrastructure. But Teradata and its new acquisitions, Aster and Aprimo seem to be working hard to make clear to the business users of an enterprise how that tech infrastructure connects well to what the business needs to accomplish in every part of the enterprise. These ideas were found in many of the Partners sessions:   

    Every business session that I attended continued to emphasize people (roles), process, practices — and positioned tech in context of serving the first three – very focused on real business outcomes

    Real collaboration permeated the projects described in the sessions – not called out as such but well exhibited in descriptions of what was done and why – shared passion for getting real things done in effective ways, teams working cross-departmentally

    Natural collaboration happens mostly in enterprises where the company ‘culture’ is open to cross-team collaboration and working to effective goals

    Purposeful and constant communication across teams is very important for the success of the projects presented

    Sessions drove home that data is only valuable in context – context that is comprised of many aspects of the business and how the data is to be used

    It is more and more essential for people to take time to understand their data sources and the data itself, before trying to use it, before integrating it and so on >> certainly before analyzing it and using it for decision-making

    The need for excellent information flow, reliable data, accurate analytics permeates every group in the enterprise, and can help these groups find more ways to innovate internal activities, as well as innovating products and services, and relationships with customers and partners

      

    Multi-faceted innovation is the basis for transforming companies into innovative, dynamic and social businesses. Most companies focus innovation activities on products and services, and on finding new markets. But to survive and thrive, companies need a strategic multi-faceted commitment to innovating throughout the enterprise, how it does business, and how it interacts with customers, employees and partners. Once such a commitment is in the works, enterprises then need to understand how information technologies play significant roles for the success of multi-faceted innovation.