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Lyndsay Wise

Hi and welcome to my blog! I look forward to bringing you weekly posts about what is happening in the world of BI, CDI and marketing performance management.

About the author >

Lyndsay is the President and Founder of WiseAnalytics, an independent analyst firm specializing in business intelligence, master data management and unstructured data. For more than seven years, she has assisted clients in business systems analysis, software selection and implementation of enterprise applications. Lyndsay conducts regular research studies, consults, writes articles and speaks about improving the value of business intelligence within organizations. She can be reached at lwise@wiseanalytics.com.

Editor's Note: More articles and resources are available in Lyndsay's BeyeNETWORK Expert Channel. Be sure to visit today!

Many BI implementations are based on a subset of business pains or initiatives within the organization. These projects serve one or a few departments and generally take into account a certain outlook already perpetuated within the organization. In many of these cases, analytics are predefined and even data discovery involves the analysis of pre-defined business rules. As these projects are rolled out, they begin to unravel. On the one hand, they address a specific set of requirements based on what departments have faced in the passed or are used to analyzing in the present. On the other hand, there is a general lack of ability to delve into issues more completely and address new issues as they occur or evaluate information in a different way.

An example that is becoming more prevalent these days is an organization’s need to develop customer-facing applications and create competitive advantage through better customer experience. A holistic approach to BI and data access is a key way to achieve this.  For instance, developing successful customer-facing applications means understanding the needs of the customer, how they interact with the tools they have access to, why they call in for support, how important of a customer they are, what their account looks like, what services they use, etc. Only by consolidating a wide variety of data sources can an organization really gain insight into their customer base. Information such as accounts receivable, customer support, transaction history, application use, and the like should be consolidated to provide account managers, call centre reps, and anyone with access to the customer insights into how to better service their customer or where to draw the line.

Obviously, customer-facing applications is just one area that requires a broader outlook when looking at the information required to provide better products and services. Whether sales, marketing, supply chain, or industry focused, organizations require the ability to analyze data that extends beyond sales pipelines, sales performance, or marketing. With mobile access, cloud based computing, and big data stores all becoming a reality and providing more flexibility in what and how information is accessed, the fact remains that unless all types of important data are easily accessible, BI remains limited.

The concept of holistic BI right now is still just a concept to many organizations, and that is ok. Not all traditional BI infrastructures can adequately handle new data types or complexities with ease. Consequently, many organizations are looking at how to restructure their outlooks and BI infrastructures to address newer challenges that apply a more holistic approach to data management and analytics. Looking at holistic BI as an iterative approach and developing a game plan on how to achieve broader data access and better customer insights is the first step to taking advantage of the full benefits BI and supporting technology now have to offer organizations.

This post was written as part of the IBM for Midsize Business program, which provides midsize businesses with the tools, expertise and solutions they need to become engines of a smarter planet. I’ve been compensated to contribute to this program, but the opinions expressed in this post are my own and don’t necessarily represent IBM’s positions, strategies or opinions.

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Posted February 28, 2014 5:32 PM
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