How to remove customer service data silos

The "big data decade" is challenging today’s CIOs to break down data silos and share information across the enterprise. This is by no means a small feat and can often be a complex process. Despite some businesses addressing this successfully, we are still seeing large amounts of structured and unstructured service-related and workforce performance data existing in call centres, regional branches and back-office environments, remain siloed.

This data is critical because it holds the true ‘voice of the customer’ and, when analysed effectively, it adds a crucial and missing component to capturing insights on their wants, needs and behaviours. It also helps create a common thread of performance data that ties together an organisation’s back-office operation, such as order fulfillment, application processing, transaction processing, billing and collections, into a single dashboard to deliver products and services faster and more cost effectively. This is the information that executives long for.

This leads to the question: how can business strategies and supporting customer service technologies integrate with the more traditional sources of enterprise data? And how can siloed data from workforce optimisation, such as quality assurance, forecasting and scheduling, and customer interaction analytics, be shared with web analytics, CRM applications, business process management (BPM), and business intelligence (BI)?

Achieving this not only helps identify cost and operating efficiencies, but also re-shapes marketing efforts, has a positive impact on customer experiences and ultimately drives profitability. Capturing the right data, transforming this into intelligence and incorporating this with workflow and BPM as part of the broader mix, outlines how businesses can integrate traditionally siloed data, and promote intelligence and information-sharing in customer service operations.

Done right, these insights can be extended into actionable intelligence that reaches far beyond service to drive corporate strategy at the highest level.

A customer’s experience depends on the ability and performance of front office workers who speak to them – whether in a shop, a bank, or on the phone to a contact centre agent.

However, these customer facing business units are like the visible tip of an iceberg. They commonly involve only one-tenth of employees, and for many organisations, the back office represents the largest opportunity for significant improvements in cost reduction and business performance. While lots of information is already available, through CRM and HR systems and telephone records, the success of these complex ‘under the waterline’ operations rely on amalgamating this data with business and performance issues being identified on the front line. To ensure front office workers are well trained and able to handle situations effectively, sophisticated workforce optimisation systems are designed to schedule self-service training programmes for developing employee’s capabilities and performance.

Knowing what customers think about the business is important, but knowing why is equally important since it helps managers understand which processes, products and services may need fixing or improving. With a workforce optimisation strategy and technology, including voice of the customer analytics software, businesses can capture this information through interactions with customers in the contact centre and across the enterprise. This goes beyond simple search and categorisation by leveraging advanced data mining technologies to tell managers why customers are contacting an organisation across a range of channels, including phone, email, web analytics and social media networks. The next step is to determine how this affects the business. 

On collecting this customer interaction and employee performance data, companies need to be able to turn it into useful and usable information. Voice of the customer analytics, such as speech, data, text, desktop and process are all tools which can help turn the insight gathered into actionable intelligence, based not just on basic customer service metrics, but on the very nuanced and subjective nature of customer service itself.

Voice of the customer analytics, such as speech analytics, can evaluate recorded audio of conversations with customers to help surface trends and opportunities, identify strengths and weaknesses with back office processes and the products themselves, and understand how offerings are perceived in the marketplace. By analysing against a semantic index (phonetic data processing and data mining matched up to a 60,000+ word dictionary), with advanced emotion detection technology that can determine and trigger action based on the mood of the caller, this software can automatically categorise and mine interactions by providing meaning and context.

To identify call scenarios that may impact performance, data analytics uses the attributes associated with the call, as well as context categories identified by speech analytics, to uncover contact situations that can positively or negatively impact a company’s ability to meet its Key Performance Indicators (KPIs). Text analytics produces similar intelligence by capturing and evaluating data generated through conversations online. Desktop and process analytics add yet another dimension by measuring application usage, and analysing workflows and processes to help improve business performance. The key is to take this information and integrate it with other types of customer interaction and performance data, such as workflow, to ensure maximum effectiveness and efficiency is achieved on all customer interactions.

Businesses use BPM and workflow systems to streamline and automate paper processing and document routing. However, these systems are limited in the intelligence they provide managers regarding workforce, capacity and resource planning. With BPM and workflow systems, managers know how much work needs to be completed (the demand side of the business process equation), but without the employee information (the supply side) a lot of questions remain unanswered. However, workforce optimisation can work in tandem with BPM and workflow systems to address the effectiveness and productivity of the people handling the work.

In addition to capturing employee desktop activity from diverse system environments, new process analytics software is capable of mapping processes and displaying the flow of work items as they move through the people and systems within a defined process. Process analytics can supplement BPM by helping gain visibility into the process steps of all users based on actual behavior data. For example, by defining the steps that make up a process; and measuring the time taken by each employee to complete each step.

To achieve all this companies need to capture, analyse and take action. First, they need to try and make sure ‘above the waterline’ data is pulled together and unified in one system. Second, delving ‘below the waterline’ can help managers understand the meaning and contexts behind interactions with customers. Third, bringing the whole together with workforce and BPM to guide how employee time is best used.

Harnessing customer data in this way allows organisations to take a ‘big data’ approach to customer service. By enabling valuable voice of the customer analytics to be shared organisation-wide, it can be used by businesses to speed up its ability to react to market opportunities, find new efficiencies in core business processes or streamline activity in order to drive greater productivity.