Managing Staffing in High Demand Variability Environments By: Dennis J. Monroe, Six Sigma Master Black Belt, Lean Master, and Vice President, Juran Institute, Inc. Many functions within a variety of businesses face the challenge of responding to customer demand which varies widely from month to month, week to week, day to day, or even hour to hour. Examples of such functions are Customer Service Call Centers, Hospital Emergency Departments, Consumer Electronics Manufacturers, and Retail Outlets, to name a few. By monitoring historical demand and its variability, such organizations can calculate and use Takt Time to determine appropriate staffing levels given different levels of demand. Flexible staffing arrangements can then be designed to allow the business to optimize the number of employees to a given level of demand. Takt Time The first factor needed to compute the required staffing is the concept of Takt Time. Takt Time is defined as the rate at which the customer will demand or purchase one unit of product or service and is calculated by: Available Time Takt Time = ------------------------ Demand Available Time represents the time, usually stated during a day, that the process could be producing outputs if needed. So, for example, in a three-shift operation where each shift has half hour paid lunch and two 15-minute breaks, the Available Time would be: 24 hr. ½ hr. ¼ hr. ¼ hr. = 23 hr. (or 1,380 min.) available in a day. The other factor in the Takt Time calculation, Demand, reflects the historical rate at which customers demand the product or service the business is providing. If Available Time is stated by the day, then Demand must also be stated as an average per day. Let s say the average daily demand over the previous one-year period for the MP3 player a company produces is 1,713 units and Available Time per day is as above (1,380 min.). Takt Time would be calculated as follows: 1380 min./day Takt Time = --------------------- =.81 min./unit (or 48.6 sec./ unit) All Rights Reserved, Juran Institute, Inc. 1
1713 units/day So, in order to meet customer demand, on average, the company must produce one MP3 player every 48.6 seconds. Demand Variability For the average Takt Time calculation to be useful, it requires a stationary demand environment. In reality, such an environment is rare. Most businesses experience variable demand over time. To stay with the example of the MP3 player manufacturer, would you expect the demand for the product to be stationary, that is to say, having little variability over time? Probably not. In the consumer electronics marketplace, demand tends to be seasonal, corresponding to the end-ofyear holiday season. What might be a typical demand pattern for this market is shown in Figure 1. How does a company deal with such variability in demand? This is accomplished by recalculating Takt Time for each significant demand shift and using that calculation to adjust staffing for each season of the demand. All Rights Reserved, Juran Institute, Inc. 2
MP3 player demand CY '08 60000 50000 40000 Units 30000 20000 10000 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Month Figure 1: MP3 player demand Calculating Staffing Using Takt Time Calculation of minimum required staffing is accomplished using the formula: Total Process Time Minimum Staffing Level = ----------------------- Takt Time To truly optimize staffing, it is first required that you have a process with work leveled, that is free from significant bottlenecks. This is difficult to achieve, so a safety factor may have to be added to the minimum staffing calculation depending on how much process inefficiency remains. This can be based on management s experience, but continuous improvement efforts All Rights Reserved, Juran Institute, Inc. 3
are important to maximize efficiency and, thereby, minimize needed staffing. In the seasonal demand scenario described above, the Takt Time for each month must be calculated in order to staff according to the season. Assuming it takes a Total Process Time of 165 minutes to produce one MP3 player, the minimum staffing level for each month could then be calculated. Table 1 reflects that calculation based on the example, and Figure 2 shows the resulting relationship of minimum staffing to demand. Month Units Days Units Per Day Takt Time (mins.) Staffing Jan 32865 21 1565 0.881789 187 Feb 24680 20 1234 1.118314 148 Mar 32032 22 1456 0.947802 174 Apr 30492 22 1386 0.995671 166 May 25662 21 1222 1.129296 146 Jun 26158 22 1189 1.160639 142 Jul 35469 21 1689 0.817052 202 Aug 41492 22 1886 0.731707 226 Sep 42462 21 2022 0.682493 242 Oct 54186 22 2463 0.560292 294 Nov 56716 22 2578 0.535299 308 Dec 31671 17 1863 0.740741 223 Table 1: Minimum Staffing for MP3 Line by Season All Rights Reserved, Juran Institute, Inc. 4
Demand vs. Staffing 60000 350 50000 300 250 40000 200 Units 30000 FTE's Units Staffing 150 20000 100 10000 50 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Month Figure 2: Demand vs. Staffing 0 Looking for the periods where demand is relatively stationary, it can be seen that there are three seasons: December through June, July through September, and October through November. By averaging the demand as shown in Table 2 and calculating the minimum staffing by season, it can be determined how many FTEs need to be added or subtracted and at what time. This can be accomplished most easily by using temporary employees to fill the gap above the base staffing level in the December through June level. Just to Complicate Matters Average Season Staffing Dec.- Jun. 169 Jul.- Sep. 223 Oct.- Nov. 301 Table 2: Seasonal Staffing All Rights Reserved, Juran Institute, Inc. 5
There are, of course, situations in which demand varies substantially over a shorter time period than in the previous example. Some businesses must deal with significant monthly, weekly, daily, and even hourly swings in demand level. The same thought process as above can be applied equally in those more volatile situations. Let s look at the example of a customer service call center. As you might imagine the demand in this setting varies significantly from hour to hour during a day. In reality, it also varies from day to day of the week, as well as on a seasonal basis like the MP3 player example. For simplicity in present discussion, let s focus on the variation within a day, for now assuming all days, weeks, and months are equal. There tends to be peak calling times during a day in a call center. The variability in the call rate, represented as calls per hour, might look like Figure 3. You can see that the number of calls received each hour varies substantially. Average Calls per Hour 180 160 140 120 Average # of Calls 100 80 60 40 20 0 00: 01: 02: 03: 04: 05: 06: 07: 08: 09: 10: 11: 12: 13: 14: 15: 16: 17: 18: 19: 20: 21: 22: 23: Hour Figure 3: Call Center Average Calls per Hour All Rights Reserved, Juran Institute, Inc. 6
Examining the hour-by-hour graph, it can be seen that there are some natural groups where the volume varies little; 02:00 to 07:00, 09:00 to 13:00, 13:00 to 18:00, and 18:00 to 22:00. It can also be noted that there are transition times where the demand changes steadily or rapidly downward or upward; 22:00 to 02:00 and 07:00 to 09:00. Assume that Available Time is 60 minutes per hour and each call takes an average of 3.8 minutes; by applying the Takt Time and staffing calculation to this daily demand pattern, the appropriate staff levels for each period of the day can be determined as shown in Table 3. Interpreting the calculations in Table 3 along with the groups and transitions discussed above, the work schedule could be: 09:00-18:00 8 people 09:00-15:00 1 additional person (part-time worker) 18:00-22:00 7 people (part-time workers) 22:00-23:00 Drop two from the 18:00-22:00 crew (leaving five) 23:00-02:00 Drop one more from the 18:00-22:00 crew (leaving four) 02:00-07:00 Remaining 4 of 18:00-22:00 crew all leave, 1 person starts (part-time worker) NOTE: staffing needs at 02:00 actually = 1.52 07:00-09:00 3 people from the 09:00-18:00 crew come in early NOTE: 07:00 hour is actually 2.5 and 08:00 hour is actually 3.7 Hour Average Calls Takt Time (mins.) Staffing 00: 59 1.02 4 01: 56 1.07 4 02: 24 2.50 2 03: 22 2.73 1 04: 20 3.00 1 05: 21 2.86 1 06: 22 2.73 1 07: 39 1.54 2 08: 59 1.02 4 09: 146 0.41 9 10: 154 0.39 10 11: 138 0.43 9 12: 145 0.41 9 13: 126 0.48 8 14: 137 0.44 9 15: 128 0.47 8 16: 133 0.45 8 17: 128 0.47 8 18: 111 0.54 7 All Rights Reserved, Juran Institute, Inc. 7
19: 106 0.57 7 20: 108 0.56 7 21: 106 0.57 7 22: 76 0.79 5 23: 68 0.88 4 Table 3: Call Center Staffing Certainly experienced managers can come up with other schedules that meet this staffing plan. The important point is that by using the calculations of staffing levels, employee costs will be minimized while maintaining customer service levels. Not All Days Are Equal With little reflection, it is probably apparent that the above example is somewhat simplified in assuming that every day s demand follows the same pattern as depicted. Some questions arise: What if each day of the week has its own distinct demand pattern? How do I maintain an acceptable service level to my customers in the face of this day-today variation in demand? There are a couple of different ways to deal with the differences between days and still maintain an acceptable level of service. The first, and possibly most obvious, is to construct a staffing plan for each day of the week based on historical demand patterns for that day. If the demand is also seasonal when looked at over a full-year period, the daily demand pattern could be measured distinctly for each season and staffing plans could be developed, stratified by day and season. It s easy to recognize that the possible permutations are nearly endless. The important thing is to use the least complex plan that still results in a reasonably acceptable level of customer service as measured by common metrics such as Time to Answer and Hang-up Rate. The second answer to the above questions could apply if the day-to-day variation in demand is not large. In that case, one can calculate the calls to be answered within a 95% Service Level (SL) or Confidence Interval (CI). All Rights Reserved, Juran Institute, Inc. 8
Begin by measuring the hourly call rate from day-to-day over a period of time, say three months. Calculate the standard deviation for each hour period, multiply by 1.96 (the Z value for 95% confidence), and add to the mean call rate. Using the 95% SL call rate instead of the average call rate, one can now calculate staffing to support the 95% SL. Those calculations are shown in Table 4. Hour Average Calls Std Dev 95% SL Takt Time (mins.) Staffing 00: 59 2.1 63 0.95 4 01: 56 2 60 1.00 4 02: 24 1.5 27 2.23 2 03: 22 1.4 25 2.42 2 04: 20 1.5 23 2.62 1 05: 21 1.3 24 2.55 1 06: 22 1.4 25 2.42 2 07: 39 1.7 42 1.42 3 08: 59 2.1 63 0.95 4 09: 146 4 154 0.39 10 10: 154 4.2 162 0.37 10 11: 138 4 146 0.41 9 12: 145 4.3 153 0.39 10 13: 126 3.8 133 0.45 8 14: 137 4 145 0.41 9 15: 128 3.9 136 0.44 9 16: 133 4.5 142 0.42 9 17: 128 3.2 134 0.45 9 18: 111 3 117 0.51 7 19: 106 3.5 113 0.53 7 20: 108 3.4 115 0.52 7 21: 106 3.1 112 0.54 7 22: 76 2.3 81 0.75 5 23: 68 2.6 73 0.82 5 Table 4: Staffing for 95% Service Level An appropriate schedule can now be established to support the revised staffing levels. If there is significant variability in the length of calls, then that could be computed to a 95% Service Level and factored into the staffing calculation in the same way. All Rights Reserved, Juran Institute, Inc. 9
Final Remarks The intention of this article was to stimulate the readers thoughts about how to more effectively staff their organizations by calculating and using Takt Time. As it should be clear by now, the actual calculations can be applied to much more complex situations than those described here. Takt Time, however, is a concept that describes an ideal, a target to work toward. Minimum Staffing calculation is of that same nature, but without targets to move toward, managers can wander aimlessly, only guessing at what the goal should be. As noted earlier, these target calculations are no substitute for experience and wisdom; they only serve to give that experience and wisdom a more empirical direction. All Rights Reserved, Juran Institute, Inc. 10