Why Simplify Is Always Good, but Simplistic is Often Insufficient
Our company has spent the last several years trying to simplify everything we do, from the method to implement products, to internal reporting, hiring, creating business cases, and more. It is always a challenge to simplify anything – there are surely cases where simplification may be contradictory to our end goal.
One such case – optimizing the workforce. (Many) Years ago, when I ‘tined’ my first optimization implementation, the client and I spent days trying to get to a good schedule, using both the % of automatic scheduling, and productivity metrics to evaluate the fruits of our labor. And when we were done, we believed we had created a great harvest of a schedule to show the users.
Without recalling the exact numbers, I do recall that our assessment overall was that we had achieved 80-85% of what the schedulers had been able to do manually, of course in about 1/100th the time…and we were both proud.
Then came the user’s evaluation. They were to take the schedule we had delivered them, and to bring it to a state that was sufficiently good to dispatch to the field. But to our surprise, it took them almost as long to make the 15-20% of changes that were necessary – and they were a lot more frustrated at the end of the day.
How could that be?
It turns out that when scheduling manually, they can develop a strategy based on the work and resources in front of them, grouping, balancing, prioritizing. However, when given a schedule that is ‘almost’ complete, trying to fit in unscheduled jobs or remove idle periods, it is far more difficult because each time you move something it has a ‘knock-on’ effect – which then takes more time to fix. “I would rather you just let me unschedule everything and start from scratch…” as the lead scheduler said, still rings in my head.
Is there a magic % of work scheduled automatically or goodness to the quality of a schedule that overcomes this problem? I’m sure there is based upon those companies that are successfully leveraging optimized and automatic scheduling today. What is it? I don’t know but I am sure that for every 1% of fixes that a scheduler has to make, the break in trust and the time to fix it must increase the risk of success by many more %’s.
How good is enough in your operation? Where does simplify need to be sacrificed for realism?