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Mining for Productivity

Mining for Productivity

/ Operations, People, Development, Technology
Mining for Productivity

How task mining and RPA can help agent productivity, and ultimately the customer experience in contact centers.

“Our call centers are extremely busy at the moment, please only call us if your query is urgent.”

The past 18 months have seen messages like this become commonplace across consumer-facing websites, shifting from those typically only displayed around major holidays to becoming permanent fixtures.

No doubt this trend has been exacerbated by the COVID-19 pandemic, but also by the ever-growing shift to online businesses, removing the physical contacts in the branches or in the stores and increasingly shifting these interactions to digital channels.

While these new channels are effective at managing many customer interactions, the key to successfully making this shift is understanding consumer activity. And then prioritize projects that transform these interactions to ensure that they are best responded to by bots online or by humans as required.

At the same time, the pandemic shift to remote or home working makes contact center agent training and improvement more challenging, impacting employee efficiency, and becoming yet another factor to throw into the mix.


Despite best efforts, there remain inefficiencies in contact centers. The combination of humans and high staff turnover, together with a wide range of constantly evolving processes that are typically based on legacy software platforms and across which agents have to navigate, is asking for trouble.

It’s an environment in which the combination of high pressure, constant changes, and system improvements can result in situations where workers may not be able to easily learn and adopt all of the correct procedures. And it can result in the development of workarounds or ways of working that are not compliant that have been created by skilled workers to get things done out of necessity.

The question for management is how do you identify these bottlenecks and workarounds so that they can be removed, making staff more efficient and improving both the customer and the employee experience?

So, what can be done in response to this set of challenges?

One answer is simply to add more contact center agents and indeed many organizations are doing just this.

However, at a time where staff retention can be an uphill struggle, there are other options to help increase efficiency in customer contact departments. Like increasing automation and deploying technologies such as chatbots, where appropriate, to enable self-service.

Another alternative is to look at simplifying long or complex processes and optimizing workloads.

But this method represents another set of challenges in a business area that is necessarily rooted in procedure.

However, the success of both these approaches lies in having the insights and data to look at customer service interactions and identify where technologies can best be deployed to maximize efficiency gains.

Automate and Streamline

Automation is central to addressing this challenge. Solutions such as chatbots to manage some customer interactions have already become hot topics within the industry, with Gartner predicting that some 70% of white-collar workers will soon interact with conversational platforms on a daily basis.

It is clear that deploying automated solutions for certain functions is already making the life of the staff at many organizations easier by increasing accuracy and efficiency as well as enabling better collaboration. They result in freeing up time for more strategic and value-added tasks such as analysis and advising on key strategic decisions.

These investments also benefit the business through decreased churn, increased productivity, reduced costs, and improved end-user satisfaction.

Actually, organizations are already seeing the benefits of automation. Now, many of them are going further by adopting bots created by using robotic process automation (RPA). However, while this method has seen global success, getting the maximum benefits means pinpointing the best candidate roles to be automated.

Task Mining vs. Process Mining

As a result of these issues there has been a lot of interest in the fields of process mining and increasingly task mining, with software companies offering solutions. Both of these perform deeper dives into the underlying processes that enable organizations to maximize the benefits from RPA.

So, in reverse order, what is task mining? And how is it different from process mining?

A simple way to describe task mining is as a technology that captures repetitive, everyday tasks that are analyzed and optimized by streamlining the steps or just automating them completely.

This can be done by identifying inefficiencies in the way that tasks are operated, stopgaps in employee training, and of workarounds to system changes and issues.

Task mining is crucial since it collects, identifies, and allows targeted automation, training, and process improvements at an organizational scale.

In contrast, process mining is an all-encompassing, end-to-end analysis of all the processes employed at an enterprise level.

A simple way to describe task mining is as a technology that captures repetitive, everyday tasks that are analyzed and optimized by streamlining the steps or just automating them completely.

Process mining tells you what processes exist throughout the business to complete the work. It can then suggest how to optimize those processes.

However, task mining works on an individual level, monitoring tasks completed on users’ desktops for more detailed analysis of those activities the employees are performing and finding ways to improve them.

By deploying task mining, organizations can boost efficiency, accuracy, and productivity—minimizing the duration of calls and therefore call wait times—which enables contact center staff to help more people in a day.

Unlike process mining, task mining has no need for costly and time-consuming integration so it can be rapidly up and running. It provides granular actionable insights on tasks within days of deployment, which also allows businesses to cut operating expenditures as a result.

Task Mining Benefits

Contact centers across a range of vertical markets are already reaping the benefits of deploying task mining software.

The data it processes can identify activities based on repetitive patterns that can be eliminated, streamlined, or automated to make cost savings and increase efficiencies.

In addition, companies frequently implement changes that were not adopted by the teams because of a lack of communication or simply because they were not implemented according to the actual operational needs of employees.

Task mining can help by identifying these areas and allowing organizations to target training to educate staff better, or, if required, improve the tasks themselves.

Task mining can also help with agent training by identifying the parts of the knowledge base where new hires spent most time during inbounds calls.

And, by enabling coaching staff to understand which content was the most important, task mining can enable companies to adjust the onboarding training accordingly.

Furthermore, task mining can reduce the inaccuracies common when manually inputting data, allowing staff to work faster and smarter.

The benefits are shorter hold times for those waiting in queue, and supporting more customers or enabling them to self-serve, and speeding up email response times.

The return on investment from implementing task mining can be significant: in some cases, over 300% over a year while freeing nearly 10% of the workforce to provide a higher quality of service or to perform other tasks.


While task mining is a great tool, we should be reminded that it is not a means to an end. It needs to be incorporated into an overarching strategy to prove useful.

Automating a faulty process may save time in the short term but is clearly not effective over the long term.

Although the task mining technology is focused on mapping the steps within a process and expediting them, businesses need to be certain that those steps lead to the required outcomes for the teams to truly benefit from the investment.

There are various options and approaches in deploying task mining, which differ from vendor to vendor. For this approach to be most effective, however, it is critical that it is deployed at scale; the greater the amount of data covered, across activities in a department, the more effective it is.

Task mining solutions that are deployed on-premise and handled locally within the existing IT infrastructure ensures data is retained and secured, rather than being sent externally to the organization: a critical issue in particular when handling sensitive customer data or in financial services industries.

All methods share in common the key areas to be captured, which include frequency of task, number of users, involved applications, and total time spent on an activity.


The challenges facing contact centers are universal, with the demand for services that has seen significant growth over the past few years, but also having finite resources with which to provide them.

Task mining alone is not the silver bullet. However, its role in helping to identify the areas for improvement is significant—giving actionable insights into how better training, improved processes, or indeed automation can help increase contact center capacity by using existing assets.

These insights are invaluable in identifying how existing systems can be better used to provide input for employee training. In fact we have seen positive feedback from employees, for whom task mining has significantly improved their experience of using existing tools.

As part of a larger strategy, it is possible to execute on these insights through better training, the increased use of chat or RPA bots, and improved software workflows and processes to significantly enhance the experience (like reducing frustrating waits) for customers and agents alike.

Robert Samanek

Robert Samanek

Robert Samanek is the CEO and Founder at UltimateSuite, the global leader in task mining software. A serial entrepreneur he is also the founder of StringData, a software developer for the financial services market.

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