How many people does it take to staff your schedule? (Part 2)

There is a short answer and a long answer to this question.  Here is a link to the short answer.

As for the long answer:

Take a look at the “short answer” in the previous blog post.  That is a good place to start.

The following should be considered to refine the number you get using the “short answer”:

  1. The cost of full-time labor matters.  How much does it cost you to pay someone for an hour of straight time?  How much does it cost you to pay for an hour of overtime?  I am not talking about “how much an employee receives.”  I’m talking about cost-to-the-company.  If you do the analysis correctly, you should find that the two costs (overtime and straight time) are within 10% of each other.  This is important because the amount of overtime you use will play a big factor in staffing levels.  For a fixed workload, the higher the overtime, the lower the staffing level you need.
  2. How much training does it take to qualify an employee for a position?  It is likely that there is a wide variance in this with regard to different positions.  Do Not use and “average”.  If you need an astrophysicist and a box stacker, an average will give you a bad number (4 years of post-graduate study for the physicist and 5 minutes for the stacker = about 2 years, on average, to train an employee).  Long training times lead to increased use of overtime and less reliance on other labor options such as temporary help.  If your workforce is staffed with highly skilled people, whose skills are easily transferable to another nearby company, then you will have to bend a more towards compensation scheduling and employee preferences for overtime so as to not lose these people.
  3. How variable is your workload?  If your workload level is flat, you will still have some fluctuations in staffing as people are on vacation or FMLA, etc.  When staffing fluctuates, you have extra staffing available or you can use overtime or you can reduce production.  Cost, degree of variability, employee preference and the nature of your operations will all play a role in determining how you staff for variability.   It’s worth noting here that the most expensive option is to over-staff or staff for peak production as this leads to frequent over-staffing which is costly. A highly variable workload tends to mean lower staffing and higher overtime.
  4. How available are alternative sources of labor? Is your workforce pro-overtime or overtime-adverse?  Is temporary or part-time labor available? If you are in Memphis and need temporary, highly skill forklift drivers, there are temp. agencies that can give you all this type of labor that you want.  However, if you need those same temporary skills in San Francisco, you may need to “grow your own.”  Can you scale back with seasonality by using shorter workweeks or voluntary layoffs?  Note: If the answer is no, the staff to the lower end and use overtime when things get busy.
  5. What about support activities?  Things like maintenance, engineering, quality shipping/receiving and administration all need to be staffed appropriately as you grow (or shrink).  There is no simple formula for how to staff these as there is often not a “straight line” relationship between staffing numbers in operations and staffing numbers for support areas.  For example, a 30% increase in operation staffing does not mean you need 30% more CFO’s.  In some areas, you may actually find that you need less support staff.  For example, maintenance struggles to fix everything on the weekend but if you go to a 24/7 schedule, maintenance can now take place any time in the week; including weekdays where it can be performed more efficiently.
  6. Are you LEAN?  It’s “old school” to think you should stockpile between cells in a value stream to ensure you never run out of product either upstream or downstream.  Instead, just-in-time is what modern operations strive for.  Many companies can maximize or throttle production using staffing alone.   This may mean you staff an area below its maximum capacity to ensure it does not outrun its value stream neighbors.
  7. What is the opportunity cost of lost time?  This must be a consideration if you are going to staff with as few people as possible.  You may save a lot of money by having fewer maintenance specialists but then you might lose even more money if you suffer downtime because you are understaffed.

Call Us and We Can Help

Call or text us today at (415) 858-8585 to discuss your operations and how we can help you solve your shift work problems. You can also complete our contact form and we will call you.

Overtime: Fact V. Fiction

It is not unusual for a company to contact us with the following idea: “If I can just put in the right schedule, I will save a ton of money on overtime.”

There is really just one condition where this is absolutely true.  If your current schedule has too many people at one part of the week and not enough people at another part of the week, the right schedule will correctly redistribute these people and you will save a ton of money.

Then there are times when this is partially true.  If your operation is expanding and the size of your workforce is fixed, then overtime will go up.  When overtime goes up the following happens: (1) The workforce makes more money, (2) The workforce becomes fatigued, (3) Productivity per person will drop, (4) The accident rate per hour will go up, (5) Quality will decrease and absenteeism and turnover will increase.

The perfect schedule will allow you to keep these from happening.  It does this by allowing you to add straight time hours to “replace” overtime hours.

Note the use of the term “replace.”

In most cases, reducing overtime means adding straight time.  From a cost perspective, the two are nearly identical.  Straight time costs include wages AND benefits as well as taxes.  Overtime costs include a premium rate and taxes.  In the end, they typically cost the company the same.  What this means is if you say, “We can eliminate $1 million a quarter in overtime costs with a better schedule!”  It is very likely that your next sentence should be “However, we will also spend $1 million a quarter in additional straight time costs.”

This is not to say you should not keep a handle on your overtime.  Too much will certainly cost you; often in disastrous ways (as noted above).  However, overtime should not be seen as the “low hanging” fruit on the road to reduced costs.

If you want to reduce your costs – increase your volume.

There is no simpler way to do it.

By the way, most companies, with level production levels find that an overtime rate between 5% and 15% is just about right.  Keep in mind, in a typical workforce, 20% of your workforce avoids all overtime.  20% of your workforce loves all the overtime they can get.  The remaining 60% will work what they feel is a fair amount.

If you want to know how your workforce feels about overtime… Ask them.  Don’t guess. Or…

 Call Us and We Can Help

Call or text us today at (415) 858-8585 to discuss your operations and how we can help you solve your shift work problems. You can also complete our contact form and we will call you.

Use Your Data — Know Your Business

Over the last 30 years, I have evaluated the operations of hundreds of manufacturing, processing, mining, and service organizations. Three things I have learned from that work:

  1. Companies know their business, but their knowledge is incomplete. They shoot targets, monitor KPIs, and compare their performance to their plans and budgets. But they don’t have time to actually think about their operations and performance.
  2. Companies have lots of data. It is not unusual to ask for real data and have a management team laugh heartily and say: “Oh, we have tons of data. So much data that you will be drowned in data.”
  3. Companies do not look at their data very much. Unfortunately, when asked what their mountain of data tells them about their operations, they go back to their targets and KPIs. They have data, but they use very little of that data because they believe there is too much data to understand what it is telling them.
  4. This lack of data analysis represents lost opportunities to compete more effectively within their industry. Some quick examples:
  • A world-wide, leading mining company was experiencing lower productivity on weekdays than weekends, resulting in more than a 7% (overall) loss in production capacity. Approximately 2% of this lost production was due to necessary operational and maintenance downtime, and the remaining 5% was unexplained. Why was it unexplained? The majority of lost production mid-week was attributed to the planned downtime. Since the available operational data had not been analyzed, there was no way to know that there was a potential to increase output by 5% by understanding and correcting the weekday operating problems. Instead, the problems were seen as insignificant. Imagine the value of improving an operation’s performance by 5% just by implementing procedures that are already in use within the organization.
  • An electronics manufacturer was experiencing over 25% lost capacity, resulting from shutdowns at lunches and breaks, on a board assembly line. In addition and for unexplained reasons, the line productivity ramped up as a day progressed, peaking mid-day on day-shift, and then fell off again as the remainder of the day was completed. This ramp-up/down phenomenon resulted in a 40% additional loss in capacity. In other words, the line capacity could have increased by an additional 65% just by operating continuously at its demonstrated peak productivity level yet no one knew the opportunity existed. Once again, imagine the impact of increasing capacity by 65% without additional investment This may push new capital investment off by years, not to mention the improved labor cost per unit impacts.

In this age of computers, these types of opportunities seem surprising. Yet it is not unusual to run into a management team that does what I sometimes think of as “managing by cocktail napkin”. Each day they face a set of problems indicated by their performance tracking measures but not really understood. They discuss possible solutions over lunch, take some notes on their cocktail napkins, finish lunch, and throw the napkins away because they still don’t understand the cause of the problems. The next day, they go through the same process all over again, never once looking at the underlying data from their operations.

With some effort and the willingness to scale a mountain of data (hundreds of thousands of data points in the cases above), the opportunities are clear. The data is available, but time for the analysis is not invested. The magnitude of these opportunities suggests that investing in this analysis will often result in a very real and fast payoff.

The bottom line here is that companies that do this type of analysis gain a competitive advantage in their industries. Since we do some of this analysis as part of our shift schedule evaluation projects, our clients benefit when they evaluate schedule alternatives. But you don’t need to be changing your schedule to do the analysis. You do need to know how to do the analysis or hire someone that knows how to do the analysis. And you should do that soon because your success is at stake.

I will be writing more about this topic over the coming months, including:

  • Looking at some example data sets and sources.
  • What questions should be asked of the data?
  • Answering these questions using some of the analysis tools already on your computer.

Of course, we are happy to help you if you would like outside help. Call or text us today at (415) 858-8585.