Inadequate Interest and Ineffective Product Experience – Analytics

By December 7, 2016Sestek

In the industry of “Interaction and Call Center”, as we all know, both in-house and outsource companies add new tools into their product portfolios by means of the opportunities provided by the technology, in the name of the optimization of processes, improvement of quality, maintenance of customer satisfaction at the highest and reducing the costs based on all mentioned parameters.

Budgets that sometimes reach thousands or millions of dollars are first grouped into instruments that are globally trending topics. Many corporate companies painstakingly apply the steps such as necessity identification, investigation process, architectural feasibility, RFP process, and deciding on the right product following a challenging process of purchase, they add such instruments in their inventories.

However, there is one question that remains to be answered: Are the painstaking efforts mentioned sufficient to acquire the desired properties from a product by means of these processes?

Right at this point, I regret to state that they are unfortunately not.


Usually the companies are unable to acquire the required benefits from the added technical properties in their inventories and the instruments that are supposed to make a substantial difference due to their structures.

It has only one reason, which is that the dedicated true owner of the instruments remains unorganized within the organization. As a result, we experience ineffective or partly effective product experiences from the systems that are procured with significant costs, due to a lack of interest. Perhaps, by means of such ineffective experiences, besides correcting the parameters that already require optimization, they result in processes that would require even more workforce for the organizations.

Big Data, Voice and Data Analytics Solutions are the leading indispensable instruments and concepts of our era for the purpose of improving the aforementioned processes and operations. Particularly in high volume interaction centers, it is naturally impossible anyhow to analyze and interpret all interactions by means of workforce. Just at this point, analytics software, which we are already familiar with and utilize, and which can guide us interpreting the numerical statistics of big data interactions, voice and data recordings of interactions by means of special instruments, are needed.

Until artificial intelligence is improved, analytics solutions alone will not yield root cause analysis results both in terms of voice and data, no matter how they are equipped with sophisticated instruments. Besides, it would not be right to expect them to perform such tasks when processes and operations specific to organizations are considered.

Even though the operations of such critical solutions are in relevant departments, usually it is failed to assign dedicated analysts who own the required knowledge and competence on the product.

In a matter of speaking, these instruments resemble play dough; it is up to you to give its final shape and tailor them to your needs.

Let us give an example to summarize the subject: Like any other analytics solutions, Speech Analytics systems as well, which have erected a significant awareness in organizations, must be operated and interpreted by analysts with experience and knowledge of root cause analysis and interpretation.

Unfortunately, while product owners with the mentioned capabilities are not assigned to the aforementioned tasks in many places, in other well-organized enterprise companies, Speech Analytics systems are operated by teams of 3, 5 or 10 work analysts apart from the product owner; moreover, they provide direct root cause analysis reports not only to call center operation, but also to other departments such as sales, marketing, and process in the organization.

Regardless how high level properties the analytics instruments have directing you to root cause analysis, it is an inevitable process that you manually interpret and analyze the output by adopting an appropriate method instead of sticking solely to the input of the product, and it will lead you to key results and enable you to obtain 100% efficiency.

Finally, I think that it is necessary to emphasize that the area of use of the product must be clearly identified, positioned and fictionalized. The analytics solutions should not especially be regarded as operational instruments, but also be positioned as strategic solutions.

Because, using these analytics solutions with superior properties for only quality management purposes for example, is one of the biggest mistakes that can ever be made.

Instead of using these products merely as quality management instrument, positioning them in a holistic manner that encompasses the entire organization processes would lead to 100% efficiency.

Haluk Yetkin / Vice President


Author Aylin Altınbaş

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