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Are You Data Rich, but Insight Poor? Turn Enterprise Communications Data into Actionable Insights

By   /  April 26, 2018  /  1 Comment

Click to learn more about author Larry Foster.

We’re in the middle of an exciting period of digital transformation. An important by-product of this transformation is the creation and collection of large amounts of digital data. Dubbed “Big Data,” it’s no surprise that this topic continues to be buzz-worthy among most disciplines across the enterprise. After all, organizations have solved many challenges using the insights lurking within the vast amounts of data they already own.

While enterprises have massive amounts of data residing in silos across their organizations, their struggle is two-fold: how to find the right key to unlock it and how to make sense of it all. Although an abundance of data exists, gleaning valuable information to make strategic decisions is difficult and has historically required expensive resources to fully analyze it.

Data alone is meaningless without the proper tools to dissect, analyze and interpret it. Data, in its purest form, is simply a fact or figure — bits of information, but not information itself. Only once data is processed, interpreted, organized, structured or presented in a meaningful way does it actually become information.

As a result, enterprises have turned to Business Intelligence solutions, which can help organizations produce the insights needed to better understand the stories hidden within these data silos.  And they’ve done it with great success, spawning an entire industry that develops technology stacks focused on creating Business Intelligence solutions to support this effort.

In the past few years, these new approaches to analyzing data have been applied to what was once a previously overlooked subset of Big Data – communications data. Forward-thinking organizations have come to recognize the immense value of insights that reside within these siloed communications data sets that include fixed-line telecom, mobile and other unified communications data. This shift is being driven largely in part by tapping into data that’s already managed by the telecom expense management (TEM) industry.

For historical context, enterprises have primarily used a TEM solution to help manage invoices, assets and improve processes, with the ultimate goal of reducing costs. As demand for greater insights into big “communications” data has increased, vendors have responded by adding a new level of transparency by embedding Business Intelligence solutions directly within their platforms.

There are many types of Business Intelligence tools leveraged within a TEM solution.  However, the four that are often used in the enterprise space are:

  • Reporting: Standard custom reports to tell you the “what,” as it relates to providing specific answers to specific questions.
  • Dashboards: Consolidated information for near real-time visibility and drill-through capability designed to illustrate high level visual summaries around specific measurements.
  • Ad-hoc Analysis: Specific database queries, that support drilling into data sets to find answers to questions that you already have. This form of BI typically requires help from a database associate (DBA).
  • Guided Analytics: A pre-developed and interactive “guided” way to organize the stories within the data, ultimately allowing you to explore the “why.” This form of data discovery and exploration doesn’t require report writers or DBAs and is designed to help enterprises find answers to questions they didn’t know they even had.

While some types of communications data have been quicker to yield obvious value from the stories they tell, other types have remained locked in their source systems. The lack of seeking a Data Strategy to discover both the obvious and less obvious stories leads to missed opportunities.

Below are considerations and takeaways for companies looking to glean insight from both the easy and hard to-get data derived from their communication channels:

  • Creating Transparency: Interactive data exploration and diagnostic Analytics empower telecom and mobility analysts by enabling them to focus on the current version of the truth as well as to execute a root-cause analysis of why it’s happening.
  • Eliminate the Data Silos: Pulling multiple communication data sources together is a big plus for creating transparency across an enterprise. Consider looking at fixed-line telephony right next to mobile, unified communications and even cloud data.
  • Self-Service is not Self-Sufficient: Self-service Analytics are great unless you get stuck spending all your time developing reports or dashboards instead of discovering value-added insights.  Guided analytics are designed to help “guide” end users to tangible insights. This approach can be leveraged as a best practice within enterprises that don’t want to spend resource or budget on recreating the wheel in report design.
  • Communications Optimization: There is an opportunity to uncover new insights from current and evolving communications vectors, including Unified Communications usage. Gaining new cost insights is the most obvious, but other opportunities include identifying patterns of usage (including overage and adoption of new functions), identifying compliance issues, managing dispute resolution and managing contract negotiation.

To summarize, the convergence of TEM and Business Intelligence has helped organizations develop a more succinct picture from their big “communications” data goldmine. By applying these best practice approaches, enterprises have solved how to unlocked the right stories to help dramatically improve their businesses. This has supported better decision making and created a whole new way to optimize usage, spend and overall management processes.

 

About the author

Larry Foster, Product Strategy and Vision at Calero Software, integrates market knowledge, strategic insight and a strong user focus to help our organization create cutting-edge products that deliver exceptional value for our customers. He also oversees our customer product advisory function. Larry held previous technology leadership positions as IT Director, Business Consultant, VP of Operations and VP GM of PAETEC Software Corp. Follow Larry and Calero: Larry LinkedIn, Calero Facebook, Calero Twitter

  • “Make sense of it all” really struck me. I find that companies like to almost hoard data but aren’t very good at doing anything with it once they have it. Maybe people are more of a problem in this scenario than we think? I have spent years in consulting work and in almost every company even individual employees became their own “data silo”. I would be curious how anyone would recommend handling that, it was always a challenge for me. Also, what do you when you don’t have the resources to implement strategies you are referring to? Are their scaled down versions for smaller companies that deal with Big Data?

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