Organisational Agility

“…every dollar we spent on agility has probably got a 10x return on every dollar spent on forecasting or scenario planning.”

A statement by Marc Engel, the Chief Supply Chain Officer of Unilever Europe, in the article “Agility Beats Forecasting when the Supply Chain is Stressed

This is how Tom prepared for the arrival of Covid-19. Well, he did not know Covid-19 was about to arrive; it was not part of the scenario planning; the forecasts showed increased demand. When iCovid-19 appeared on the radar everyone said not to worry.

Tom was however familiar with daily disruptions: sales not matching forecasts; supply problems; attendance issues; machine vagaries; load shedding and who knows what else.

Tom understood that to create a new “plan” that took the changes into account that the factory would need to be able to reschedule frequently and then get the factory to work to the new schedule.

Tom saw that the process of obtaining data, rescheduling, and issuing schedules was far too slow. Staff were doing their best, but it required substantial manual effort to try and switch to new schedules.

They tried stock buffering as a way of reducing the need for rescheduling; occasionally trapping raw materials in the wrong sales unit as well as incurring obsolescence as a result of sales not matching forecast or due to shelf-life expiries. Buffering did not work as well as expected.

To cater for the uncertainties of his world Tom digitalized operations. Not just randomly, with an IOT here and an IOT there, but with the specific focus to achieve the following

  • To make data available within the system, for use in decision making, current and trustworthy.
  • To shorten the decision-making process so that the factory could react faster to “unexpected learning opportunities”.
  • To be able to publish schedules more quickly to all departments / staff (and suppliers) who could be affected, to ensure synchronized execution.

Tom’s desk plaque holds a quote from Mike Tyson and a reminder of his overall objective

Everybody has a plan until they get hit”

How quickly can you recover?

Customer service, productivity and profitability are up. Covid-19 is just another day in Tom’s world.

The Role of Advanced Production Scheduling

To be able to make decisions more quickly Tom required a scheduling tool that would

  • Take minimal time to run – It needed to generate an actionable schedule in seconds.
  • Generate a schedule using their rules and considerations
  • Offer “drag and drop” and rollbacks.
  • Facilitate and store what-if schedules to enable comparisons between schedules.
  • Be easy to understand and use, with easy use of colour to help understanding.
  • Be able to work with their current and future systems.

After evaluating various alternatives Tom selected the Siemens Opcenter APS solution, as it met the above criteria and could be configured and extended to meet their needs.

To ensure schedule integrity, Tom understood that the schedule would need to access data that was both correct and current.

Tom used the issues encountered when generating schedules to drive method and procedure changes in supporting areas.

Often these changes required the introduction of new technology e.g. they needed to implement a shop floor feedback solution to ensure that the system contained the current status of jobs in progress in production, for use by the scheduling solution.

It was interesting to note what an impact improved scheduling had on the business, with initial payback only taking a few months.

Pressure was exerted on the procurement department and on suppliers to provide feedback to support decision making,

Improving and keeping data accuracy was a key focus in all areas.

Once they had an agreed schedule, they could issue it in seconds, via electronic means.

Being hit by an unexpected change was often painful, recovering was not fun and often included heavy breathing sessions. Over time it got easier to do. 

Melting of the Frozen Zone

Once the factory had the scheduling process under control, which was not perfect in the beginning, but better than what they had before, they began to schedule more often. Initially they created a daily schedule, then a new schedule prior to every shift start then, if called for, they found that they could even reschedule within shifts.

This flexibility meant that they could reduce frozen zones. When they started the frozen zone was a rolling 5 days, now it is two shifts. The first to allow for raw material picking and preparation and the second for production. Now they can change the mix of the 3rd shift without sewing confusion in the stores and plant.

 This also meant that they could replan more often. For A items, they could replan daily to take the major deviations between actuals and forecasted sales into account wrt to stocks. Planning being how much to make when and scheduling being in which sequence to make it to minimize setups, washdowns, etc.

This capability has meant that they are much more flexible and are able to avoid potential problems while also being able to take more of the opportunities that have arisen.

Of note is that this increased flexibility has meant that they have been able to reduce finished goods stock holding without compromising service levels.

Extended Supply Chain Visibility

Tom remembers when they first started, they only had visibility of stocks within their control and Procurements best guess of the delivery date and quantity of purchase orders. Often however when recovering from a hit they needed to know where their supplier was with respect to delivery of their orders e.g. had they been shipped but not yet received; had they been manufactured but not yet shipped, were they in progress already, when were their orders planned to enter production.

It took a while to get key suppliers to supply updates from their systems and then to incorporate this information into the scheduling solution in a meaningful way.

The result has been worth the time and effort invested as recovery decisions have often hinged on this knowledge.

In return for the supplier data the factory has shared production demand timing to allow the supplier to better understand the factory’s demand timing.

They are developing the same degree of visibility with their key customers, to make sure that they are in a better position to service their needs as well.