There are many small and mid sized businesses (SMB) in manufacturing that design, engineer and manufacture complex custom parts and assemblies. For such companies manufacturing overhead cost can be quite significant and they face challenges in dynamically tracking and forecasting manufacturing overhead costs in the presence of variances. As one of our customers correctly put it “when manufacturing overhead costs are a significant portion of your overall costs, the health of the company depends upon knowing, tracking and understanding it”. SMBs usually require some guidance in developing standardized models for overhead cost modeling and tracking.

Business Objectives:

For example, the previously mentioned customer has assembled data internally and has identified important variables which potentially influence manufacturing overhead (MO) cost structure. However, they would like to enhance their understanding of MO costs and develop real time tracking capabilities for MO costs. Specifically, for them the objectives are:

  1. To verify manufacturing overhead accounting is done according to generally accepted standards
  2. To develop a means to extract data from the ERP system, perform the manufacturing overhead calculation automatically and post it to a dynamic dashboard
  3. To track key factors which drive/control manufacturing overhead (visualize trends)
  4. To run what-if studies on MO: what would happen if overtime was extended, what would happen if machine hours were reduced and so on.

A systematic approach to solution:

After review and mutual agreement regarding the business objectives, we usually adopt the following process:

Step 1 – Develop the manufacturing overhead cost model:

First, we review internal data that are relevant to MO calculation based on client’s experiences. Second, we build an initial manufacturing overhead cost model based on standard procedures (e.g., revenue based, head count based, or transaction based) and compare to client’s existing models, if any. In the above case, for example the client uses a machine hours (activity based) manufacturing overhead model. 

Step 2 – Data Extraction and Preparation

After agreeing upon the best model for MO costs, we will then need to work with client team to develop processes for automatic extraction of data from their ERP systems to feed the dashboard. This involves writing SQL type scripts to automate pulling data from client environment and couple it to the dashboard.

Step 3 – Develop dashboard for tracking Manufacturing Overhead cost:

The dynamic dashboard will receive regular (daily or weekly) updates from the processes that work with the ERP system and reflect MO costs. Such a dashboard might typically have two views: a standard real time view and an exploratory “what-if” view. The standard view page may need to be expanded to have additional drill down capabilities for MO costs. The What-if view page will have sliders and selectors to allow client to conduct quick studies of the impact of changes in MO cost drivers on the overall MO cost.  A concept dashboard with the two views is shown below. View 1 on the left allows a real time tracking. View 2 on the right will allow running “what-if” studies on MO.

Step 4 – Installation, Testing and Integration:

The final step is to test the manufacturing overhead cost model, data extraction processes, and the ERP-to-dashboard data coupling. This requires installing and test the dashboard on the client’s laptop or desktop. 

Finally, some specific features of such dashboards might require manual entry options for the following two cases:

  1. An average activity level in machine hours per week if manufacturing overhead costs are calculated on machine hours basis.
  2. An “X” factor such as machine repair or other unplanned costs which typically bring the productivity down and thus drive the manufacturing overhead costs up

The bottom line with manufacturing and even many services based companies is that overhead costs are a significant factor which influences business health. Analytics for tracking and understanding such factors is not a luxury but indeed a necessity.

Originally posted on Thu, Aug 16, 2012 @ 08:35 AM

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