In Analytics

Businesses and other enterprises invest in advanced analytics and situational awareness solutions to improve operations.  The value of this investment typically equates to one or more of the following benefits: customer satisfaction and retention, competitive advantage, cost savings, productivity improvement, workflow consistency and business agility, as well as being more responsive to actual or likely problems, failures, service disruptions, and crises.  The value and benefits are often visible, measurable and aligned with the impetus for installing the solution.

Other ongoing secondary benefits and value from these solutions can come about by happenstance, arising organically when end-users have an “a-ha moment” and apply their system, data, and/or other resources to purposes other than what it was originally intended.  Another serendipitous way of finding value is by performing “what if” analyses.  These types of secondary benefits come about by finding value hidden in your data.

Finding value hidden in your data brings about substantial benefits because many small optimal decisions and corresponding favorable outcomes can equal or exceed gains from a single large-scope optimal decision or action.  This is especially true if the smaller optimal decisions are repeatable and support recurring situations.  Benefits such as these do indeed positively impact top-line revenues, bottom-line earnings, and the common key performance areas that I listed in the opening paragraph.

Consider that your data may be generated from multiple systems and stored in databases and repositories that are a tightly coupled component of those systems.  As an example, your purchase transaction data is in an order management system, your production data is in an ERP system, your financial data is in a general ledger system, your customer support interactions are in a CRM system and your customer loyalty program data is in yet another system.  Some of these systems may run in-house and others in the cloud.  They may even be located in different geographies, including different countries.  Hence your difficulty in seeing or readily finding value in all of your data.

There is correlation between most if not all of your data.  Each purchase has a correlation to the production data, the financial data, the loyalty data, and possibly the customer support data.  However, because the data is often in various formats, systems, repositories, and locations, it’s impossible for a human to sift through the data to find either overt or subtle correlations that reveal the value hidden in your data.  The situation is exacerbated by data streaming from Internet of Things (IoT) devices.

These same issues also make it challenging for data processing systems, including analytics and business intelligence (BI), to find value hidden in your data.  Data processing systems should be up to the challenge, given their strength – performing highly repetitive and iterative tasks involving large amounts of data.  However, finding value hidden in data, especially if that data is spread across systems and in silos, requires specific architectures and technologies to overcome these challenges.

Identifying correlated items and events is more likely to occur, and occur more often, by architectures and technologies that aggregate data from multiple sources and feed that data to advanced analytics, machine learning, pattern matching, statistical methods and complex models.  Such correlations lead to value that can be found and brought forward for decision-making and action.

Here are some examples of found and realized value that was hidden in data:

  • Awareness of not using the most economical way of transporting items, and adjusting accordingly
  • Identification of excess cargo capacity while optimizing shipping routes
  • Identification of assets most likely to fail by drilling-down into key performance indicators

If you have found and benefited from finding value hidden in your data, please share your “eureka” story with us.

For more on this topic of finding value hidden in your data, please see the article “Through the Looking Glass: Critical Asset Insight and Transparency Increases Operational Efficiencies & Customer Confidence.

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