A World Transformed

A World Transformed – Stratalytica™

In Analytics Age, Stratalytica™ by Stratalytigist0 Comments

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In the first issue of Stratalytica, we noted that, in 2012, 2.5 quintillion bytes of data were created every single day. Viawest, a privately held data storage company, puts this number into perspective.  Numerically, 2.5 quintillion bytes of data looks like this 1,000,000,000,000,000.000, or (2.5 x 1018).  As a visual equivalent, imagine 57 billion iPads stacked atop each other (each with 32 GB storage space). These “bytes” are big data numbers Big data numbers will continue to grow as data-enabled devices become ubiquitous, collecting data on everything and everyone.

The October 2013 Harvard Review article, Big Data: The Management Revolution, states that companies characterizing themselves as data-driven perform better on objective measures of financial and operational results.  In particular, “companies in the top third of their industry in the use of data-driven decision making were, on average, 5% more productive and 6% more profitable than their competitors.”

That preceding statement is important, not only because of the contrast that it provides regarding the success of data-driven companies, but also because it highlights a subtle shift in language that the current discussion around big data ignores.  Thriving in the Age of Big Data does not require mastering big data.  Thriving requires mastering analytics, which is why InterNuntius calls this the Analytics Age.

Yes, big data is driving the transformation, but big data is a phenomenon only because organizations lack the necessary data architecture and infrastructure to handle big data issues.  Much of the conversation surrounding big data is irrelevant because the bulk of big data will be completely unusable in a business sense.  Overcoming the performance gap requires an integrated Enterprise Analytics Environment.

It bears repeating that executives in leading companies focus on mastery of analytics. Why? Because analytics provides the insight needed to formulate strategy and to power innovation. Executives in leading companies understand that being insight-driven is the real key for executive performance in the Analytics Age.  The truth is that there is a profound amount of power for strategic innovation found in your integrated enterprise data.

Enterprise Analytics differs from Web Analytics and from Big Data Analytics in 3 fundamental areas:

  • Enterprise Analytics requires an Integrated Analytics Environment. Both Web and Big Data Analytics are typically stand-alone analytics systems. They’re stand-alone because enterprise data has been impossible to integrate, until now
  • Big Data

We say it this way:

Insight (the mined value inherent within the data) is one of the primary drivers of corporate value.

In the not too distant past, the role of the executive was to lead in the area of strategy development for the purpose of maximizing shareholder value.  The Analytics Age Executive has the same mandate; the only difference is that the Analytics Age Executive has better tools.  In addition to maximizing shareholder value, the Analytics Age Executive has a secondary mandate – to utilize available insights to maximize corporate and shareholder value through insight-driven innovation.

  • Connector.

    Establish a mandate to be insight-driven

    Understand that being insight-driven necessitates organizational, process, system, and operational transformation.

  • Connector.

    Understand that establishing an insight-driven organization will require investment

    After establishing a mandate to be insight-driven, understand that establishing an insight-driven organization will require investment in updating your data infrastructure. This is a senior leadership initiative and should not be delegated to I.T., no matter how tempted you are to do so. This new normal requires a comprehensive, integrated data architecture with commitment from each business unit AND business system. It is impossible to make effective insight-driven decisions with siloed data. Input from senior leadership is required to ensure that strategy, critical success factors, and key business indicators are integrated into the data architecture.

  • Connector.

    Develop baseline reports and analysis

    Once your integrated data architecture is in place, develop baseline reports and analysis of the integrated data to establish a foundation for more sophisticated analytics such as data mining and predictive analytics models.

  • Connector.

    Establish strategic and innovation portfolios

    Using insight developed from your integrated data, establish enterprise or functional business unit level strategic and innovation portfolios. Require data as a foundation for decision-making, but be open to informed anecdotal evidence.

  • Connector.

    Educate senior leadership on Analytics Age perspectives

    Ensure that all senior leadership gets educated on Analytics Age perspectives. If you find any senior leadership resistant to the changes required by the Analytics Age, let them go. You are better off having them work for your competitors.

Conclusion

The Analytics Age Executive understands that being insight-driven is the key to maintaining and growing corporate value. Mastering analytics provides organizations with the data necessary to formulate strategy and to develop an innovation portfolio.  Understanding and education are vital in developing the Analytics Age perspectives that will allow for transforming a finely tuned understanding of the interaction between the company and the marketplace into innovation powered competitive advantage.  Nevertheless, companies wishing to thrive must establish the mandate to be insight-driven and must follow-up on that mandate with an investment in an integrated data architecture that will allow for a holistic view of an organization’s inherent value assets.