Category: Supply Chain Planning

In our last post we considered Execution in the context of Planning and Scheduling; now, let’s summarize our findings and consider why and how we uniquely consider these domains.

To accomplish an objective we plan: we break our objective down into a series of steps we can follow to achieve it efficiently. We include sufficient detail to reasonably ensuring feasibility, more detail in earlier steps. We measure how well our plan meets our objective, how well we’re following our plan, and re-plan remaining steps as circumstances change. The better we plan, the more likely we’ll succeed.

We schedule when efficient task sequences aren’t obvious. Finding an optimal schedule is likely impractical, so we often use specialized logic and tools to help us out, looking for good answers fast. “A bad schedule from a good plan is better than a great schedule from a bad plan.” (S. Sidhu, i2)

We plan/schedule to help us execute: to do the right things at the right times in the right ways to efficiently achieve our objective. We freeze the portion of our plan/schedule required to preserve prep time and leave it out of our re-planning/scheduling workflow, managing reality real-time during execution.

For several key reasons, we consider these three domains separately and uniquely.

1. The objective in each domain is unique, so the tools and logic employed in each should suit the relevant objective.
2. The horizon in each domain is unique: Planning considers the entire unfrozen horizon; Scheduling considers an initial, smaller unfrozen horizon within the plan; Execution considers the frozen period.
3. The measure of success in each domain is unique: Planning considers the final objective(s); Scheduling considers localized efficiencies within the plan context, and Execution considers work quality and conformance to the plan/schedule.
4. The detail required in each domain is unique: Planning has just enough detail to reasonably ensure high level, overall plan feasibility; Scheduling requires significantly more detail to ensure efficiency and executability; Execution must manage to all of reality in real time.

Planning, Scheduling and Execution: considering planning theory and recognizing similarities, differences, and interdependencies helps us position the proper skill sets, logic, tools, workflows and data within each domain, and to integrate them effectively to ensure success.

In our last post we considered Scheduling in the context of Planning; now, let’s explore how both Planning and Scheduling enable Execution, noting their respective roles and analyzing their interdependencies.

We plan/schedule to help us execute: to do the right things at the right times in the right ways to efficiently achieve an objective. But in a dynamic world we’re constantly adjusting plans/schedules to reflect reality, which begs a key question: What parts of a plan/schedule can we change without sacrificing productivity?

We want our plan/schedule to reflect reality as much as possible, but we also need sufficient plan stability to avoid generating waste, getting ready to perform one task and then doing something else. So, inside this lead time we don’t re-plan (except for major disruptions, when such waste is warranted), and work with older data. This first part of the plan belongs to Execution, defining a frozen period, a boundary enabling us to consistently re-align our plans with reality without sacrificing efficiency.

Planning/Scheduling workflows need an accurate picture of the conditions expected at the Execution boundary, at the end of the frozen period. Given this starting condition, re-planning/scheduling can align plans with Execution, closely reflecting reality without destabilizing our work environment. When Execution experiences a major disruption, requiring a relaxation of all or part of the frozen period to enable more complete re-planning, execution and planning/scheduling workflows and interfaces should be designed to provide this capability.

Though planners may request visibility to frozen plan details within planning/scheduling workflows, such detail is irrelevant for planning/scheduling purposes. Providing it can actually be problematic since planning/scheduling tools generally approximate reality, not fully considering execution-level detail. Execution may work the plan/schedule in ways that violate simplistic constraints and interdependencies inherent in the system-generated plan/schedule, making accurate representation in planning/scheduling systems very difficult or impossible, encumbering and possibly destabilizing planning/scheduling workflows.

Now that we’ve explored planning theory and analyzed the relationships and interdependencies between Planning, Scheduling and Execution, in our final post we’ll take a step back and look at the big picture to summarize what we’ve found and why it’s important.

In our last post we considered planning theory as a unique problem solving domain, so now let’s compare and contrast Planning and Scheduling, understanding how they work together.

In most every plan we’re following a series of steps, tasks following one after another, where task order is driven by their interdependencies. But when we have some flexibility and certain task sequences are much better than others, then we have a separate scheduling problem within our planning activity that deserves special attention.

Scheduling looks at small subsets of tasks within our overall plan, within a much shorter horizon, considering much more detail and using different measures, to generate efficient task sequences. It requires a completely different skill set and supporting capability than Planning.

For example, say we have some jobs lined up and hourly employees staffed to do them; each job has multiple steps that can be done in any order by anyone, but our staff has varying pay grades and skill sets, each being much more efficient at certain kinds of work. We want jobs done on time with the least cost.

We start by planning, sorting jobs by need time and estimating how many staff we need each week based job types and historical patterns. Then we task our trusty scheduler with finding least-cost weekly assignments, utilizing each worker between 20 and 60 hours per week, completing all jobs on time. In week one we plan four people to do a set of five jobs, each having three steps; if our scheduler evaluates ten thousand schedules per second, we’ll have the least-cost schedule for that first week in … (4*15!/[1E5*3600*24*365] = ) … 16 years!

Every type of scheduling problem is different, but we know in general that they’re notoriously difficult to solve optimally, being in an altogether different space than planning. Their difficulty is often completely independent of planning complexity, and varies enormously by problem type and size. We need good answers fast, not perfect answers, using common-sense rules of thumb to simplify problems and very specialized optimization tools to do the heavy lifting.

And we can’t forget that every scheduling problem is embedded within some kind of planning problem, and that the inputs to our scheduling problems come from our plans: “A bad schedule from a good plan is better than a great schedule from a bad plan.” (Sanjiv Sidhu, i2 Technologies co-founder)

Next we’ll explore how Execution fits in with both Planning and Scheduling.

In our first post we looked at the general theory of Planning, Scheduling and Execution in the context of daily life, in a way we can all relate to. Now let’s look at Planning theory in more detail.

We plan so we can see how to accomplish a given objective, so we know what needs to be done and when, so we don’t overlook anything important along the way. The more complex our objective is, the more critical our plan will be; the better we plan the more likely we are to succeed.

The foundation of Planning, especially in complex scenarios, lies in our ability to break down an objective into a series of steps we can follow to achieve it. Insufficient detail may confuse us, where we don’t know what’s next or we forget something; too much detail wastes time on things that should be obvious and that may change by the time we get there. Knowing how much detail to include is as much an art as it is a science, it’s dependent on context, and often involves a bit of trial and error.

To create a good plan we need to identify the key steps needed to reach our goal, and we need to understand and respect the interdependencies between these steps. We need to estimate, aggregate and summarize key details supporting these steps so we can reasonably and quickly ensure plan feasibility. When there are multiple ways to do certain things we need the ability to quickly evaluate our options and pick the best ones, and in dynamic or uncertain environments we need to plan for contingencies. We also need a way to measure how well our plan is achieving our objective, a way to monitor how well we’re doing as we execute, and an efficient way to re-plan when we’re getting off track.

Obviously, given the complexities we often face, the above is much easier said than done. Keeping our approach as simple as possible while achieving our objective is important, but certain kinds of complexities can indeed be quite helpful when we’re repeatedly challenged with the same kinds of planning problems: automating data collection, reporting and optimization can free us up to do the things we do best — analyzing situations, making strategic decisions and managing our business.

Next we’ll see how Scheduling fits with Planning and Execution.

To get anything done, call this execution, we need a plan. In simple cases we might not even notice we’re planning, but we always do. All of life’s this way, all day, every day, if we stop and think about it.

And as we execute to a plan, life happens and we re-evaluate and adjust: we re-plan as needed and continue executing until we either meet our objective or give up. Whether we’re running errands, building a house, fighting a war, or managing a supply chain, the same basic principles apply.

As our objectives become more complex so do our plans. We break our objective down into key steps, considering critical baseline conditions, and include enough detail to ensure feasibility as well as we can. We know things will change, so we include more detail in earlier stages where less change is expected, planning far enough out to see how we’ll ultimately achieve our objectives.

Most every plan requires set of tasks to be done in a sequence. When the sequence is intuitive we may not even think about it, but if there’s some flexibility, and it appears that certain sequences will be much more efficient than others, we’ll likely do some scheduling. We initially plan these tasks at a high level, lumping them into periods where we need them, then as we get closer we include more detail and apply additional skill and logic to determine a good sequence within the context of our plan. This is definitely a kind of planning, but a completely different, more intense kind.

Finally, some tasks require a bit of lead time to prep for, so we “freeze” this initial part of our plans, stabilizing them long enough to protect this setup effort once we get it started. We generally handle minor adjustments during this frozen period as needed, on the fly as we’re working out our plan.

The above concepts are intuitive, and perhaps deceptively simple; it’s what we do naturally every day. But the ideas are extremely powerful when applied in larger contexts. It should come as no surprise then that they comprise the foundation of general planning theory. To be successful in more complex scenarios, where managing all the moving parts at once and seeing how they’re all working together is next to impossible, it’s important to intelligently and consistently apply these same basic principles.

In our next post, we’ll take a closer look at Planning as a unique problem solving domain, consider its purpose and scope and distinguish it from both Scheduling and Execution. Then we’ll follow with similar analyses to complete the total picture, and then summarize what we find. When we’re done, we should have a much better sense of how to tackle our most complex planning challenges.