I recently spoke with 1to1 Magazine editor Ginger Conlon about the importance of actionable insight within customer service departments and provided a few examples of how this helps deliver considerable ROI.

Injecting actionable insight into the process of resolving customer issues is a goal that most companies seek to achieve. At a high level, most business executives intuitively appreciate the relationship between a better understanding of customer issues and needs, and its impact on higher sales or greater client satisfaction.

Literally speaking, insight means gaining an accurate and deep understanding of something, for example a business situation such as a customer issue and its solution.

“Gaining insight” can consume more than 50% of the customer service department budget

The driver is quite obvious. For many companies, product diversity, complexity, and pace of change is increasing, and hence often more than 50% of their customer service bandwidth (we have even seen figures north of 70%) is consumed by activities associated with gaining understanding into customer issues and seeking a satisfactory solution for every single one; or basically customers (self-service) or agents consuming time gaining insight, and accumulating delays and frustration.

The currency of customer service is time. When you consider the cost per agent, per year of approximately $80K to $120K (fully loaded), my simple math computes this task of “gaining insight” at as much as $5M per year for a 100-agent customer service department. The more complex customer issues are the greater that costs are. We’re talking a great deal of money here.

The impact of insight challenges within customer service – we call it insight deficit – also goes beyond that direct expense. Insight deficit has huge ramifications on client dissatisfaction due to an inability to resolve customer issues fast enough and in a quality manner. It impacts revenue and reputational capital. Smarter companies will also understand its impact on agent dissatisfaction driving up costly turnover, hiring, training, quality, etc.

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In both cases, typically the actors don’t know better, or don’t have the requisite knowledge and information to act optimally, and the results show. For sales it means less revenue, for services it means lower customer satisfaction, and in both areas it means increased costs–everything businesses don’t want!

In my 25 years of being involved with IT and business process re-engineering initiatives, I have seen businesses dramatically improve their ability to manage and govern customer related information. I have seen them implement systems that capture events and transactions almost flawlessly. In fact, this has not only caused information volumes to explode, but also the diversity and number of information sources to increase dramatically.

While information regarding customers, projects and products is so meticulously captured, stored, managed and governed, users keep complaining about its value in supporting their decision making: “What do I need to do next to support the business optimally, maximize revenues, lower costs, increase customer satisfaction? How do I connect the dots between the sea and diversity of information at my disposal?”

-  How can a sales person know what to sell, when to sell, what the client needs, who should be involved, who is satisfied, who is not, who needs what, who knows who, who is the expert?

-  How can a customer find better answers via online self-service when their need is multi-faceted?

-  How can a customer service agent figure out the root cause of a complex customer issue which is not documented in a knowledge base?

Every time the answer is “they can’t,” it means inefficiency and/or ineffectiveness. It affects revenues, costs, and satisfaction.

Despite a dominant strategy to consolidate systems and information silos over the past two decades, the fact is that on average, companies have twice the number of different information sources versus only 10 years ago. Moreover, no one had predicted the growth of unstructured information, and no one had predicted that a significant part of an organization’s valuable business information would reside outside the firewall and totally outside of the CIO’s control.

Heterogeneity of IT environments is the new norm, and at the current pace of change, IT budgets can’t keep up with the information consolidation vision, the perfectly integrated world, the seamlessly connected business silos, etc. As a result, users are confronted with multiple systems and logins, and their ability to obtain the integrated and relevant views of information they need is much less than optimal.

In sales and services this is a critical problem. “Wait! Our new integrated system will do just that!” Well… in the meantime if systems cannot be integrated easily, how can decision support be made available?

This is what Enterprise Search 2.0 helps achieve through unified indexing: Enterprise Search 2.0 isolates the user from all the complexity of IT systems under the hood, and gives users what they need. Fundamentally, the function of an Enterprise Search 2.0 Platform is to aggregate intelligence from disparate digital sources—in order to provide decision support in every area of the business, making them more efficient (time savings) and more effective (better quality).

Decision support must be interactive in order to facilitate and inform business decision-making activities – to help identify and solve problems or make decisions in management, operations, customer service, sales, engineering, etc. – by compiling useful information from a combination of raw data, documents, knowledge and people, or other business information. That is a mouthful! In simple terms, it means providing the business user with the knowledge they need so that they can sell or service customers more efficiently – time savings – and in a more effective way – better satisfaction.

I’ll continue to explore the fundamentals of a decision support system in my upcoming posts, including a four-prong framework that defines how the user interacts with and leverages information for decision support.

Stay tuned…

Republished with permission of author from original post.