Employee Productivity Suite

Don CarltonDon Carlton Personal Systems Services Category ManagerFounding Analyst | Scholar ✭✭

With so many folks now working from home does anyone have knowledge of an employee productivity analytics tool? This is going to sound a bit big brother-e, but I have long thought that a analytics tool that would keep up with things like call time, emails sent, number of participants in those email responses, and the number of emails read along with the time where the desktop (during the work hours) that are idle along with other types of desktop activity might be a good team management tool (if managed properly). I am not an advocate of micro-management, but have seen various examples of these types of measures and did not know if a full suite exists. Thoughts?

Answers

  • Joe ThomasJoe Thomas Analytics Evangelist Founding Analyst | Scholar ✭✭

    hmmmm, interesting thought, you'd need to be connecting your device management software with your CRM and I'd bet a pretty terrifying amount of logfile data, but I know I've seen these types of analytics available from call center vendors.

    I can tell you at FinancialForce, we've seen developer productivity (# of bugs and bug resolution time lowering, code and feature "volume" increasing) improving since WFH was implemented in March. I can't speak to outbound/collaboration metrics.

  • Patrick BoycePatrick Boyce Workforce and Reporting Manager Member

    We were confronted with the same task about year ago; here's what we have done:


    We have 2 methods of capturing productivity:

    Front Line Agents:

    These are agents whose time is mostly spent answering phone calls and emails. For these agents, their time in different states (Ready, talking, meeting, etc) is captured automatically via our telephony system. We present that data in a dashboard with the ability to drill down to an individual agent or day.

    The main metrics we focus on on the individual level are: Tasks per productive hour (the most relatable metric for an agent to understand), AHT (And how that time is spent between talk and wrap time), and Internal Shrinkage (the % of login time lost to non-productive time like breaks, meeting, unscheduled breaks).

    Our Tier 3 handles calls and emails as well, but they also complete tasks not captured by calls or emails while they are in ready. To account for this, we use a simple SharePoint list where they can capture time spent doing tasks unrelated to calls/emails. We remove the time spent completing these tasks from their related ready time, so that when they are presented with their tasks per hour, it is limited specifically to the time they had available to work on calls/emails.

    The collection and presentation of data is automated through SQL queries and Power BI.


    Non-Front Line Agents:

    These are agents who complete little to no front line tasks. For these agents, they track all their time in their outlook calendars. For each different meeting, they have different categories to classify the meeting regarding it's topic, related product, and goal. That is to say, 1 meeting can have an associated topic, multiple goals and multiple products.

    At the start of each month, they export their outlook calendar as a csv file and save it to a network drive.

    An R script accesses the folder, reads all the CSV files and merges them into a single dataset.

    In the event the agent selected multiple categories, the meeting is broken into a new row for each category combination. The meeting duration is evenly distributed amongst all selected categories. (IE if a meeting was 1 hour, and related to 2 different products, there will now be 2 rows for each product, and each row will be attributed .5 hours)

    The script then creates a dataset that determines each agents scheduled time by day according to their hire date, end date and region specific holidays.

    The data is then summarized by month (Month | Agent | Hours Worked | Topic | Goal | Product | Hours Scheduled) and then the total hours are forecasted with the Prophet forecasting package, using the hours scheduled as a regressor.

    All data is loaded into Power BI for presentation and all tasks completed within our CRM tool are also added to the data.

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