Sales Planning Using Master Production Schedule

To successfully implement a Master Production Schedule (MPS), it must be understood that its purpose is not to state the quantities and delivery times of the products. The MPS is in fact a solid contract between Sales and Production. The MPS defines what Production will produce, and it’s not a forecast at all.

Here’s how MPS is used for Sales Planning:

Sales Planning – Challenges in the 21st Century

• Sustaining long-term relationships with Customers is a key factor in today’s
  competitive business environment
• Two significant blockers in meeting the above expectations is to consistently deliver Customer required Products in requisite quality and in Customer committed Schedules
• Meeting Quality requirements set by the Customer is a subjective and hence relatively a more complex problem to address
• Establishing a simpler and feasible approach to meeting Customer Committed Schedules is within the reach of most Organizations

Meeting Customer Schedule Commitments

•  In an era of Demand exceeding Supply, your Marketing / Sales Functions bring Orders for Products to your Organization – Demand
• Committing a feasible Delivery Schedule in response to the Demand is the joint responsibility of the Planning + Production + Inventory Functions
• Deriving a best-fit Schedule, the combined Team needs to have, at their finger-tips, Constraints such as
  ○ Available Product Stock
  ○ A reasonably scientific idea of Production Capacity (which is Finite)
  ○ Available Raw-Material for a proposed Time-Period
• Without a tool backed with Data, the Team is handicapped to understand these Constraints and hence Customer Committed Schedules are made based on Rule-of-Thumb

Effects of Not Meeting Schedule Commitments

• Using the Rule-of-Thumb approach, there is a likelihood of not being able to meet Customer Commitments on Schedule
• Most Customers will retain loyalty even if you do not commit to their expected Schedules, as long as you demonstrate the fine ability to meet the Schedule Commitments you have pro-actively promised
• When you fail to deliver on Time, a Customer who has a choice between you and your competitor (who both supply at presumably the same price and quality), will depend more and more on your Competitor when you fail to meet your Schedule Commitments

We need to move away from this Rule-of-Thumb approach and use scientific, data backed Tools and methods before committing Customer Delivery Schedules

Sales Planning – Concepts

Sales Planning – Balancing Demand vs. Capacity

Demand Planning = Telescopic -> Microscopic View

Purpose
Approaching the fulfillment of Customer Demand placed on RPT needs a 3-Step Methodology – Planning, Scheduling and Loading

• Planning -> At time of accepting a Customer Order, a method to identify whether the RPT Resource Profile is in a position
  ○ to meet the required Delivery Schedule or
  ○ need to shuffle other Customer Orders depending on Priority or
  ○ committing a more pragmatic Delivery Schedule.
• Generally adopted in the Time-Horizon of Month-in-Advance
•  Scheduling -> Given the committed Delivery Schedule as per Planning, a method to schedule different Jobs at different WIP Stages, in consideration of Resource Availability. Generally adopted in the Time-Horizon of Week-in-Advance
• Loading -> Given the Week-Plan, identify specific Jobs on specific Machines with necessary additional resources (Operator, J-F-T, ..). Results in a Job-Card. Generally adopted in the TimeHorizon of One-Day-in-Advance

Planning Horizons

Sales Planning – Defining Capacity

Demand Planning -> Use Cases

Definitions
Order Book Period -> is the Time-bucket in which the Orders are received and precedes the Production
Time-Bucket by your Product Lead Time. As an example, if your Product Lead Time is 2 Months, then
your Order Book Period is two months in advance of your Production Time Bucket

Order-Book Period (Time=t0) :- As Customer Orders stream in for a specific Time-Bucket, your ERP
Tool systematically fills the stated Capacity

• At Time=t1, as we progress in receiving Customer Orders in the Order-Book Period, it is likely that
  the next Order for a Product in a Product Group, fitting it into the Time-Bucket will lead to exceeding
  the stated Capacity. System informs you with a Red Alert. In this situation, we have choices to
  address this challenge
  • Communicate a feasible later Time-Bucket as fit based on Capacity – to Customer – and get his Acceptance
  • If Customer demands Delivery in the current Time-Bucket, re-Prioritize other Customer Orders with the same Product Group Demand, so as to fit in this Customer Order Demand
  • Increase Capacity (temporarily) – Adding Shifts, Rotating Load on Machines / Work Centers,…

Demand Planning -> Use Cases

• At Time=t2, in the Order-Book Period, it is likely that the next Order for a Product in a Product Group, fitting it into the Time-Bucket will result in Demand being -/+ a pre-determined percentage of the stated Capacity. System informs you with a Yellow Alert
• At Time=t3, close to the end of the Order Book Period, System determines that the Capacity is in excess of the Demand for a given Product Group. System informs you with a Green Alert. In this situation, we have choices to address this other kind of challenge
  ○ Inform Marketing / Sales to increase efforts to fill the Capacity for the identified Product Group
  ○ Identify Make-to-Stock so as to fill the Capacity
  ○ Reduce the Capacity – divert to other Product Group Demand so as to balance the Load

Defining Capacity -> Queries & Doubts

• How to set these initial quantitative numbers of Capacity by Product Group ?
  • There are basically two approaches, as below :-
    ■ A scientific method applying principles of Time-Study, Load Balancing and Through-Put
    ■ Start with your Rule-of Thumb (!)
•  Stated Capacity set initially may vary with time, how to reset this Number ?
  ○ With an established ERP System, the post-Production Module provides Numbers actually
  produced for a given Product Group in a Production Time-Bucket
  ○ We can use this input to analyze and reset the Capacity definitions
  ○ Essentially, this is a Closed-Loop-Feedback mechanism as represented in the next slide

Redefining Capacity – using ERP

Overview

Sample Sales Plan – Dashboard View

Sales Planning – Conclusions

• An ERP System, backed by static and dynamic data is essential to planning Production to meet the competitive nature of today’s Customer Demand
• Rule-of-Thumb approaches are Risk-Prone
• Once your Organization has embarked on adopting the proposed approach of using ERP, it is essential to monitor the results – we should follow the universally accepted Deming Principle – Plan  Do  Check  Act (PDCA)
• The PDCA monitoring mechanism will help to understand what needs to be
  tweaked, improved, areas of Innovation, so on and so forth

About the Author

• Subodh, currently serving as Founder Director of 3CIT Consulting, based out of Bangalore has a rich and varied background in ERP Consulting
• He has managed more than 100 ERP Assignments, in various roles, ranging from Design, Development, Implementation in the initial phases to ERP Requirements Engineering, Process Change Management in the recent past
• Subodh has exposure to the world leading ERP Software Platforms such as SAP, Oracle and BAAN. At the same time, he has participated in ERP Projects involving Open-Source ERP solutions such as Odoo (OpenERP)
• Subodh is currently engaged with guiding Advaya Softech in the Design & Development of their flagship Software product, Blaze