An iSixSigma Case Study By 1 comment A young, rapidly expanding financial services company located in India runs an in-house help desk for responding to customer queries via email or telephone. Help desk response time is tracked using software that calculates the time between registering and closing calls. A project was instituted to train employees in the relevant tools and techniques of Six Sigma and Lean methodologies in order to achieve dramatic improvements in the help desk operations.
The senior manager of the Help Desk, Dot Gifford, has established a team to address short-term forecasting. The Help Desk currently handles approximately calls a week from over 50 different internal processes and organizational units.
The team has several additional items to discern in addition to the short-term forecasting of call volume and must be ready to review all items at an Informal presentation in 10 days time.
As a exult, the CARS must be able to handle customer concerns by making the customer feel as if they are their only priority. Because of this requirement, Cars will need to be highly independent and self motivated when it comes to addressing the customers needs.
The ability of a potential CARS to handle multiple concerns at a time will need to be demonstrated prior to selection. Additionally, once trained, the CARS will need to have the ability to make decisions on their level as much s possible to provide the customer a sense of confidence that they are speaking to the right person for their problem.
Keeping can c R engaged In ten dally routine wall De Key to having an effective Help Desk experience for the customer. Management will need to provide not only an effective compensation package to retain Cars, but will need to regularly recognize consistent service excellence and those occasions where a CARS provides an outstanding service experience.
As Ford and Bowen point out, the management team of the Help Desk need to ensure each CARS is producing customer solutions through memorable experiences. Help Desk Mission Statement The next question for the team is to define the mission statement and create an verbal strategy for the Help Desk.
Based on this definition, the Help Desk could define their mission statement as: From this mission statement we can create our strategy, which is closely tied into the characteristics of the CARS Job itself. Our customers are not simply the person who contacted us, but the banking customer they are representing who put their faith and trust in our institution.
With these tools now available to the Help Desk team, when a customer calls with an error from an inaccurate stock price we are now able to handle this concern in a proactive approach. By being proactive, the help desk is acting upon their mission statement and strategy as defined above.
The CARS, once contacted now is in control of the experience and is able to set expectations for the customer. Forecasting Short-term Demand To forecast the Help Desks call demand, the team will need to identify a few key items. As identified by Dot Gifford, the team is looking o forecast the short-term demand for the call center.
Because we are looking at data based on a time series of daily call volume, we will create a forecast of the call demand using a time bucket value equal to days. As we begin to create our forecast, we need to remember that any forecast is subject to errors.
In the forecasting techniques we are evaluating, mean square error MSIE is being used. Using this accuracy measurement, we will look for the technique that provides us the lowest MSIE Walt ten closes t Allocates Detente ten actual dally calls receiver forecasted amount.
The advantage of this technique over MA is that past data is not forgotten, but Just weighted less in comparison to more recent data.
Using a smoothing constant between O and 1 controls this effect. The closer you move towards 1, the more emphasis you place on recent data. Exhibit 2 shows that using a smoothing constant of 0. Based upon the results of the two forecasting techniques, I would recommend using SEES with a smoothing constant of 0.
As the preferred method in the short term. The reason that I suggest limited use of this particular model is due to the large smoothing constant. Ideally, a smoothing constant of 0.
Because cost is an additional constraint for the Help Desk, I would recommend evaluating the forecast and time bucket over the upcoming weeks. By adjusting the time bucket, the Help Desk should be able to improve the forecast accuracy and reduce the smoothing constant to a more acceptable level.Featured Case Study: Fault Reduction in Cable Industry.
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Case-based reasoning (CBR), a system for laying out composite parts to be baked in an industrial convection oven. CBR has been used extensively in help desk applications such as the Compaq SMART system and has found a major application area in the health sciences.
Learn how HappyFox email ticketing system improved the help desk performance of Accelerate Education, an US based online education institution. Case Study Multi-site law firm focused on growth with no tolerance for downtime. AT A GLANCE Company Ianniello, Anderson, P.C.
settlement services, and representing clients in New York’s Capital Region for over 40 years. Case Study 1: Transforming the Organization Due Week 5 and worth points Congratulations!
The executives are taking your information system proposal seriously. In fact, they think it has the potential to transform the way the organization works. Or, is your legacy service desk system too hard to modify and update without disrupting users?
The business has grown, added new staff and sites, and you need a way to reduce calls, implement new processes, deliver services, and support users with systems that help keep you afloat.