At a contact center, alarm bells clanged when it was suddenly observed that the wait times shot up by 2x, and resolution time by 4x. This raised several red flags in the reports and dashboards. However, beyond that observation, the traditional reports could not provide intelligence as to why was this happening and what action should be taken to mitigate it. Which capability do they need to be best geared for such eventualities?
Unique challenges of managing data-driven contact centers
The challenges of managing a customer contact center are like no other business. There is little control over demand forecast, and if it goes haywire, resources must be deployed in tandem to meet SLAs. Customers can choose any day, time or channel—voice, chat, e-mail or even switch between them–and expect continuity and consistence of service.
Service quality is highly people dependent. Overworked agents result in burnouts and high-resolution times. CXOs need to continuously monitor and optimize to balance between resource slackness and stress. Moreover, multi-location centers develop data silos, sometimes fragmenting a single customer account. To plan for every cycle, data is often collected in multiple spreadsheets which need to be manually collated. This results in delays and errors, ensuing in a lack of trust. Analytics derived from this data are limited in scope and not reliable enough to help on-ground decision support.
Addressing challenges with Workforce Management solutions
A modern Workforce Management (WFM) solution addresses this complexity. It builds a trusted ecosystem and provides CXOs with decision support in a timely manner. Companies that focus on process efficiency and revenue maximization use a WFM solution to manage scheduling their workforce in line with forecasted workloads, rostering, tracking and optimizing time on the job as well as employee absenteeism. The operative words here are efficiency and optimization. WFM addresses the need to match the forecasted volumes with the optimal number of resources who possess the right skills. It avoids overscheduling which leads to higher costs, and under scheduling that results in customer dissatisfaction and revenue loss.
Introducing static reports
WFM software integrates a business analytics and intelligence module that supports executive decision making. These modules have built-in static reports and dashboards which track key parameters that monitor business health. Often hard coded by analysts and developers and automated to be distributed periodically to the management team, these built-in reports are a great tool that provides a snapshot of the business and trendlines from the aggregated data.
Static reports are great for management reviews and to make strategic decisions on the business direction.
However, static reports have limitations in terms of their applicability, and CXOs of data driven contact centers rely on ad hoc repots to optimize their operational agility. When data analysts build reports, their focus tends to be on the data and not the visualization and hence, the report formats tend to be unintuitive numbers on a spreadsheet. This can be compounded by static reports being hard coded instead of reporting tools, making alterations by the business user nearly impossible.
Ad hoc reports supplement static reports
Operations are ever dynamic and unpredictable and functional managers need information and decision support to deal with the current and emerging situations. Line managers need to make operative decisions on a day-to-day basis. They need reports of what happened yesterday, last summer or during the last holiday season, and intelligence from analysis of this data to take immediate decisions to optimize the next shift, day or week. They need to drill down from the aggregated data into root cause and take corrective actions or adjust maximize efficiency. They also need real time answers to their queries to understand the insights hidden within the data.
Functional Managers cannot rely on static reports alone which are timed and analytics that are periodic as they provide a limited snapshot of a pre-decided slice of data. This is where ad hoc reports play a vital role to empower non-technical business users to use data to get answers to their business questions in real time, without any dependency on the IT team.
Ad hoc reports are created quickly “as needed”. Ad hoc reporting tools do not need users to have any knowledge of coding or query language and are operated in self-service mode, building reports from scratch. This means that the GUIs are highly user friendly and intuitive.
Static and ad hoc report comparatives
The infographic compares Static and Ad hoc reports and their usage:
|Static / Canned Reports||Ad hoc Reports|
|Periodicity||Pre-decided, Weekly, Monthly or Quarterly or Annual||Any time, on need basis|
|Audience||Pre-decided as per distribution list||Created by/shared with audience and stakeholders on a case-to-case basis|
|Generation||Automated||Manually, in self-service mode|
|Frequency||Repeats as per schedule||One-time|
|Format||Often text-based, with tables of aggregated data to show trends||Highly Visual and user friendly to support agile decision making|
|Ability to code||Required||Not required|
|Customizable by users||No||Yes|
Ad hoc reporting for WFM
The true power of WFM solution is unleashed when managers use ad hoc reporting to get real-time insights from real-time data, that can be immediately acted upon. Ad hoc reports and analytics pulled out from WFM software must be real-time to be a useful decision support tool for users. For example, canned reports generated at the end of day or shift are of no use in managing intra-day workload variations. Also, these reports must integrate data in real-time from all sources may they be at different geographical locations, or multiple contact channels like e-mail, chat or calls.
Ad hoc analysis is a business intelligence process that lets users dig deeper into the objective data to find answers to specific business questions that would help in decision making. WFM solutions integrate a BI module that uses advanced analytics, preferably with AI and ML capabilities. They have inbuilt analytics and drill-down capabilities that help in understanding the root cause of unplanned events and deviations, and to take decisions about corrective actions.
What makes a good ad hoc reporting tool?
Ad hoc reporting tools also have self-service analytics capability and integrate data from various sources using built-in data management tools. Additionally, ad hoc reports present information visually which makes it easy to quickly grasp and act. This is an important to minimize time lag in understanding the real story hidden in the data.
WFM users should be able to create these reports on-the-fly as needed to support agile decision making. Despite the challenges of using disparate data types or sources, running ad hoc queries, and ad hoc analytics and reports should be generated with no time lag.
To summarize, an ad hoc reporting and analysis tools for WFM should have:
Use-cases of ad hoc reporting and analysis
Consider these ad hoc report examples that illustrate where it scores as an important decision-making tool in managing operations.
- A monthly or quarterly sales report for a company presents aggregated trends and shows that sales revenues are consistent. However, an ad hoc report pulled by the sales head shows that the western region sales is declining, though it’s balanced by a corresponding increase in eastern region. A further drill down into western region data using self-service analytics provide more insights on this drop attributing it to declining orders from large volume customers, or salespersons who previously contributed higher revenues. Armed with this knowledge, the sales head can pull the right levers to turn around the situation, acting immediately.
- A contact center supports customers of multiple products of a company. The average call volume is 15,000 calls/day, with an average resolution time of 2.5 mins. The team is well trained on the products, and the resource plan is optimized to meet an average wait time of less than a minute. The key SLA metrics are captured by the periodic static reports and monitored by the VPs and stakeholders. Suddenly, it was observed that the wait times shot up by 2x, and resolution time by 4x. This raised an immediate red flag in the reports and dashboards. However, beyond that observation, the traditional reports could not provide intelligence as to why was this happening and what action should be taken to mitigate it.To understand the root cause, the WFM managers used ad hoc reports, breaking down call reports by shifts, agents, products, time of the day and centers. These reports made it clear that there was exponential increase in the call volumes for one of products, along with a high-resolution time which effected the overall performance. Ad hoc reporting was used to trace the root cause to a feature change in a newly launched model, which was not user-friendly and resulted in an increased the number of support calls.To resolve, calls pertaining to the new model were routed to a dedicated resource team culled out from the existing team. The rest of the team maintained the SLAs for the other products, while the new product team were monitored using a different matrix agreed with the customer.
Ad hoc reports within WFM software empowers decision making in call centers
Let’s now take a deeper look into how WFM along with ad hoc analytics can be a very powerful tool managing operations in a customer contact center. Four areas that are crucial to managing a contact center effectively and where managers benefit from using decision support tools are:
Forecasted workloads are predicted from historical call volumes across multiple contact centers and touchpoints. However, for better accuracy, forecasts need to be altered dynamically based on emerging trends, patterns and black swan events. Organizations that continue to use spreadsheets for forecasting are impacted by their ability to handle large volumes and data types. Besides, merging several sheets slows down the forecasting process severely. WFM solutions have tools for forecasting and ad hoc analysis using Auto ML algorithms which consider subtilities like inclusion, exclusion or scaling of identified outliers that continuously improve accuracy over subsequent cycles.
Scheduling follows forecasting and when done right, has the maximum opportunity of impacting costs and customer delight. Good scheduling practices makes the right staff available for interactions and manage queues of varying customer types effectively. Effective scheduling does not stress agents and keeps them motivated and happy. Smart Managers use ad hoc reporting tools integrated with ML algorithms to match arrival patterns with staffing needs, control leakages and plan shifts on need basis- may they be full-time or part-time.
Traditional reports and analytics have limitations when compared to dynamically planned rosters. WFM modules empower managers to create rosters incorporating multiple factors like business rules, skill set of agents and their performance, outliers, leaves and work timings. Moreover, business intelligence modules within WFM solutions use the power of AI to match the best agent with every customer interaction. While static reports raise performance alerts, ad hoc analytics help in taking proactive action to mitigate situations as they evolve, instead of post-facto analysis and reactive action.
A key parameter that is tracked in all call centers is “adherence”. It refers to ensuring that committed service levels are met, even when the unforeseen happens. It is important to anticipate the unexpected and to dynamically change forecast and scheduling to stay within agreed service levels during each shift or time interval/cycle. Static reports are of little help in managing adherence, as drilling down into patterns is important to gather important insights. Using ad hoc analysis to empower decision makers yields insights that trigger immediate corrective actions.
Modern customer interaction centers are data-driven and proactively managed to avoid employee burnouts while adhering to and exceeding customer satisfaction scores. A contact center’s cycles are in constant change, with planning processes that need to constantly keep up with optimizing resources and maintaining service levels. They must deal with dynamically changing workloads, hence mid-shift corrections need to be made on the fly while maintaining compliance with HR and business rules along with employee preferences. A WFM solution equipped with AI and AutoML based ad hoc reporting and analysis capabilities can prove to be an invaluable tool that plays a crucial role in providing managers with decision support and intelligence at every step.