Behind the Scenes: Unraveling the Magic of Capacity Planning.

Transcription

1 Behind the Scenes: Unraveling the Magic of Capacity Planning

2 Contents Introduction 3 Laying the Groundwork: Our Business Challenge 3 The Devil s in the Details 4 Traditional Solutions 6 The Best Practice Solution 7 Summary 9 2

3 Introduction This unique guide will walk you through a step-by-step discovery of what really goes into capacity planning taking you behind the scenes and helping you make sense of this complex concept. It will also offer some best practice guidelines for maintaining and managing this aspect of the scheduling process. Laying the Groundwork: Our Business Challenge In order to really understand the concept of capacity planning, its power and potential pitfalls, we ll walk through an example. Let s imagine we are a part of a service organization that uses appointment booking for our field resources. Our organization has a wide variety of job types including new installations and repair. Each of these job types has different priority, urgency and agreed service level. For example, our organization has agreed to complete new installations within five days and repair faults in two. As an organization, we have some high-level goals: 99Offer customer commitments that we can keep 99Maximize our field resources time 99Reduce travel costs 99Shorten our customers waiting time To help us reach our goals, there are three primary components that our organization will need to understand: 1. Demand the expected service jobs per day, including type and location 2. Field Resources the mobile workforce, including their skills and availability 3. Time what service level agreements (SLAs) are in place These components make up the equation that is capacity planning. But we ll come back to this in a bit. Determined to provide a quality service, on time, we are faced with some steep business challenges, including: What is our expected demand for a given time period? Do we have enough capacity to fulfill the expected demand on time? Can the organization meet the agreed service level with the resources available? If not, what service level can be achieved? What is the best way to balance the expected demand against our available resources? In other words, how many jobs should we perform every day and of which type in order to fulfill the demand on time? If we are unable to fulfill the demand on time and need more capacity, what is the best way to get it? If we have both internal field resources and subcontractors, how much work should be allocated to each group? In order to address these challenges and provide the superior customer service we desire, we have outlined a series of stages that we ll need to go through: Stage 1. Define: How many jobs are done each day, of each type This stage allows us to distribute the demand based on our available capacity. For example: if we expect to get 20 install jobs on Monday, we can book these anytime during the week and still meet the required SLA of five days. We will just need to decide how many of them can be completed each day. This is the demand side of the equation. Stage 2. What SLA can be achieved? Our above example had 20 install jobs coming in on Monday. But what if we had 40? This would increase our SLA to around seven days. Stage 3. Adjust Capacity If the SLA is not in alignment with our business goals, we ll need to add more capacity. Stage 4. Re-Distribute and Re-Assess Go back to stage 1; re-distribute the work and review the impact on the SLA in stage

4 The Devil s in the Details Using our example company and the ground we have set, let s look at some example pitfalls that are likely to arise. Capacity Limitation Let s try to perform stage 1 in the example above. There are two task types, install and repairs. The SLA for new installations is five days and for faults is two days. Typically, install appointments are booked further in advance then faults. What this typically means is that new installations consume the majority of the available slots far in advance, leaving little to no time for faults. This requires us to limit the number of new installs that can be done each day by a certain percentage, in order to leave capacity for repairs. This concept is known as capacity limitation. However, the percentage capacity limitation must be absolutely accurate. If the percentage of the capacity limitation for installs is too high, we still risk not having the necessary capacity to complete repairs within our SLA of two days. On the other hand, if the percentage is too small then we run the risk that new installations could be blocked, rejected or delayed. This becomes a back and forth, tug of war: Missing SLAs vs. White Spaces in the schedule where lost capacity equals idle time and low resource utilization. The Complexity of Accurate Capacity Limitation So what is the right percentage? This is dependent on several key variables, including: Expected Demand How many service calls will the service organization get for each task type every day? Available Capacity How many field resources are there? What is their availability? Skills Mix How many field resources can perform the various tasks? For example: new installations only, repairs only and both new installations and repairs? A Working Example Let s take a look again at our example organization, and attempt to determine the capacity limitation for new installation appointments using a practical example. First, we ll collect all the expected new installation appointments that are expected to be booked. Task Type Expected Demand Mon Tue Wed Thu Fri Installations Remember, we ll need to leave enough space to complete repair tasks as well. So we ll put those at the end of the week on Thursday and Friday. So here is the forecast, we ve laid ours out in a GANNT chart: Mon Tue Wed Thu Fri New Installations 10 tasks New Installations 15 tasks New Installations 20 tasks New Installations 17 tasks Repairs 8 tasks New Installations 23 tasks Repairs 8 tasks To make things simple, let s assume that each task takes one hour regardless of type. With our team of three field resources, our available capacity and skills mix is: Resource Skill Available Capacity Mon Tue Wed Thu Fri Ann Installations OFF 8 Mike Installations & repairs Pay special attention to different task types as they often compete on the same capacity. 4 OFF Wendy Repairs

5 The Devil s in the Details Based on this, what is the right capacity limitation percentage for each day? As you can see the answer isn t easy. What we can easily see is that we ll need to perform repair Remember our SLA jobs throughout the week not is five days for new just on Thursday and Friday installations and in order to make the most of two for repairs. our resources and meet SLAs. Although they will not compete on the capacity on Friday but they can impact the Installs task that do compete on the capacity on Friday. After taking all these considerations into account resource availability, skill sets, available capacity and expected demand it is possible, however difficult, to define the right percent of capacity limitation for each day. Working out the capacity limitation for each day once isn t enough though. You need to continually update it to factor in unpredicted scenarios, including: The actual bookings today were more/less than expected This means that the available capacity for the following days is now different than planned and will impact the capacity limitation percent s. Unplanned absences These reduce the available capacity within the day as well as the skills mix. Other HR changes Example: A new field resource may be joining the team or perhaps an engineer has left. This can also cover relocations. Another example is the adding of new skills to field resources or perhaps a skill set has expired due to a lack of recertification. Changes in subcontractors available capacity Changes in priority Example: In bad weather conditions we may want to delay all installs to the next week and focus on the repairs only. Or, as part of a marketing campaign we may want to promise installation by three days instead of five. These unpredicted scenarios mean that you ll need to re-calculate the right capacity limitation percentages daily and maintain them according to the actual booking and the updated capacity. This is definitely not something that can be done manually. We ve only used a basic example in our company. We had two task types what if we had ten? Or thousands of resources? What about differentiating between different Want a Challenge? Play our W6 Game online and see if you have what it takes to be a top scheduler! w6game.clicksoftware.com customer types? For example, the service level for a platinum customer is two days for installation. What about differentiating between population densities? For example the service level in urban areas is two days and in rural areas it s three. In reality the problem is much larger than our simplified example. And this is only stage 1 of solving the problem! 5

6 Traditional Solutions Generally speaking the existing solutions for capacity planning are based on one or more of the following concepts: 1. Balancing the demand against buckets of capacity By far the most common, a bucket of capacity reflects the collective capacity of field resources with the same skills set. Using the example above, in our service organization there are 3 buckets of capacity: 1) the field resources that can do only installs, 2) the field resources that can do only faults and the field resources that can do both installs and faults. 2. Manual definition of the capacity limitation percentages 3. Using historical data to set the baseline for the capacity limitation percentages These concepts do not provide a solution for capacity management that is either accurate or effective. The buckets concept accumulates all field resources that have the same skills set. If an organization has a large number of different skill sets there may be a very large number Just how ineffective is the bucket approach? Check out our video online: truth-based-appointmentbooking of buckets. In some extreme cases it s possible that every engineer will have a unique skills set (in the field of medical equipment for example) and the term bucket becomes really individual. In addition, there are some business scenarios while the bucket concept doesn t cover. For example, if there is a minimal set of skills that all field resources must have and there are jobs that only require the minimal skill level. This creates a scenario where is no specific bucket for minimal skills capacity since all field resources have additional skills on top of their other skill sets. Another good example is a case where a task requires two field resources, one to do the job with a certain skill and one to assist; where his or her skills don t really matter. In this case it is not possible to define what bucket provides the capacity for the second field resource. Manual definition of capacity limitation percentage creates numerous problems. First, it is difficult to know what the optimal capacity limitation percentage is. This can be severely damaging to the process as we discovered earlier in this guide. Second, there is a need to manually create not just the capacity limitation, but several other key percentage variables, including: quantities of tasks per tasks type, customer types, product (when relevant), territory and date. Third, there is a need to maintain these percentages daily in order to capture the fluctuations of demand, availability and other business conditions. Last but not least, when defining the percentages manually you have zero visibility into the knock on effect this will have on the service level. You will have no clear indication of whether or not expected tasks will be performed on time and what the end service level that can be achieved will be. Using historical data to set the baseline for the capacity limitation percentages is also highly ineffective. For service organizations worldwide; every day is unique. The demand varies from day-to-day, as do the other key variables in determining capacity limitations: unplanned absences, training, resource turnover, marketing campaigns, equipment upgrades, product offerings, traffic and for some industries including utilities and communications service providers severe weather. There are just too many variables to say that capacity for today will be the same that is was a year previous. 6

7 The Best Practice Solution Your business is a flexible, fast paced machine and in order to operate at its most optimal it requires a solution for capacity planning that is automated, smart and accurate. Having understood challenges in capacity planning and the pitfalls in most modern mythologies; let s take a detailed look the best practice approach: simulation. Simulation The requirement is to have a system that calculates the capacity limitation percentages automatically and optimally. One that can: Provide the expected service level Compare it with the target See every field resource a unique individual with a unique skills set See every day as a unique day and recalculate during the day of service to provide the actual capacity A tool that can do all of the above is referred to as simulation. Simulation takes the forecast (expected demands) and the required service level as input. It then takes into account actual bookings and all information from the field resources, including skills, availability, etc. Using this data it calculates the optimal capacity limitation percentages and simulates the scheduling or the appointment booking process returning a service level as a result. If the service level is not good enough, adjustments can be made adding more capacity and re-running the simulation again to see the impact. A Standard Simulation Workflow 1. Update At the end of the working day the simulation is updated with current data for: actual bookings, information from the field, travel times, demand forecast and if applicable the service level target. 2. Run The simulation is run, automatically defining the capacity limitation percentage. No manual intervention is needed to calculate or set these percentages. They are the optimal figures. 3. Review Results Evaluate the expected service level by looking at the simulation results; compare them to the service level target. 4. Key Indicators If the service level is acceptable excellent; otherwise the simulation results will reveal how much capacity is missing, where, when and for what skill sets. 5. Adjust Add capacity by using subcontractors or overtime, relocate resources, or remove un-necessary absences. At this stage what if scenarios can be factored in to see how the effect capacity and the service level. 6. Re-run The simulation is run again using the adjustments to insure that service level is acceptable. 7. Communicate The operational scheduling system is updated with the capacity limitation percentages, this will directly impact the appointment booking process. If you are not using a solution for appointment booking then this step can be skipped. The Beauty of Simulation Solutions that are based on the simulation mythology like ClickSoftware s Capacity Planning App provide the closet analysis to reality, as they take into account any and all scheduling considerations that could potentially impact the capacity. There are no problems dealing with various skill sets, in fact every field resources could have the same unique skill set, as the simulation treats each engineer as an individual regardless. Scenarios like minimal skills or multiple field resources per tasks can be modeled using your standard scheduling process. Using the capacity buckets approached covered earlier, it was not possible to module such scenarios. On the other hand with simulation these scenarios don t require any special treatment, the silmulation just schedules the tasks and they are treated by the scheduling algorithm as if it were a real schedule on the day of service. This gives you a clear and accurate picture of what your scenario would result in. 7

8 The Best Practice Solution There is also no problem incorporating changes in demand, actual bookings, priority changes, forecast updates or any change in a field resources availability or skill as the simulation can just be run again and with updated data, providing the most up to date capacity limitation percentage. It also provides accurate data as to how many tasks meet the service level target and how many don t. Clearly outlining what capacity is missing. This allows for SLAs that are very granular, for example: per task type, product, customer type, location or date. This level of granularity doesn t add any complexity to the simulation since it simply schedules tasks by their due date whatever that may be. The simulation can also provide measures about the optimal split of capacity allocation between internal field resources and subcontractors if needed. 8

9 Summary Usually organizations purchase a scheduling system to achieve two targets: 1. Reduce operational expense by increasing resource efficiency 2. Increase customer satisfaction by increasing the service level If there is not enough capacity to perform a certain task type it will not be possible to meet the service level target, no matter how smart the scheduling solution is. If there is too much capacity it will not be possible to use resources in the most efficient way, no matter how smart the solution is. A capacity planning solution directs the scheduling system to consume just enough capacity for each task type, product, customer type, location and time. This will not only ensure the most efficient use of your resources, but that the service level is met every day, everywhere and in any business scenario. About the Capacity Planning App The Capacity Planning App from ClickSoftware enables businesses to plan available resources and anticipated demand to deliver on promised Service Level Agreements (SLAs) and meet compliance standards. Whether the challenge is controlling overtime or use of contractors, or adjusting staffing levels, especially in seasonal environments, proper capacity planning will bring forecast and true demand into balance. About the ClickAppStore The ClickAppStore is an enterprise app store made exclusively for ClickSoftware solutions. From this unique repository, users and implementers can build business processes using ClickApps to provide additional, completely integrated functionality without having to write code or go through a lengthy upgrade process. All of the ClickApps have been created to ensure you get the most out of your scheduling and mobile implementation. This growing library of apps contains solutions for: effectively planning to meet demand, achieving promised SLAs, streamlining communications, keeping the field safe, the gamification of change management, simplified timesheet tracking, increasing productivity and empowering mobile users with modern tools that help to provide great customer service. For more information about mobile workforce management and how we can help you achieve real business benefits contact ClickSoftware. ClickSoftware Offices North America +1 (888) , +1 (781) Latin America United Kingdom +44 (0) Israel Germany +49 (0) India Australia +61 (0) Visit us online at: 9