The Importance of Relevant Data In A Value Stream Map (2024)

Every business needs to make changes to its processes at regular intervals in order to continue to run smoothly, take advantage of new equipment, software, processes, or practices. Lean management is a method of management that is beneficial in many industries, so identifying areas of optimization within the business and improving them can save both time and money for a business. Identifying where these improvements can be made and the payoff these improvements can make is the role of a Value Stream Map.

Relevant Data in a Value Stream Map

When compiling a Value Stream Map it is essential to include all the relevant data to provide an accurate and up to date map. The data measures that need to be included are:

  • Inventory levels – sellable stock and ‘cushion/safety stock’
  • Production times per product
  • Up-time such as on-demand machine consumption
  • Staff levels
  • Shifts worked
  • Net available working time – daily working time minus lunch and break times
  • Scrap rate
  • Batch Size

These data measures need to be up to date measures rather than ‘historical’ measures where possible. They must also include any timings or other system data that you use to save time. Once accurate measures are obtained they can be added to the Value Stream Mapping in ‘data boxes’.

Once all of this is completed, you are ready to step back and look at what improvements are needed to the process. You can compare different products and work out a better work schedule for different work stations in order to achieve optimum efficiency within the business.

VSM Improvements – Bottlenecks and efficiency

One thing many businesses try to do is cut back on the time their customers have to wait for a product or service. A value stream map, when containing all the relevant information, can identify where in the process the product/service is being delayed, using the timeline aspect of the map.

Looking at the amount of uptime, production time per each step and the batch size travelling through that step can show which steps take longer than others. Isolating areas that may be wasting time or causing bottleneck situations in order to plan improvements. These improvements include reducing the batch sizes, or creating secondary workstations to manage the batch size. It may also include better training of staff, or updating equipment to improve the efficiency of the step.

If the step involved is caused by an outside source, such as delivery company or awaiting on supplies, new resources can be researched and attempted to improve the step’s efficiency. Improvements can include, but not limited to: bulk ordering in advance, change in delivery company or hiring of a backup delivery company.

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Example illustration of a bottleneck in a manufacturing material flow. Image Credit: Wikipedia

VSM Improvements – Streamline the process flow

When looking to streamline the delivery process of a product or service to the customer a value stream map can show the areas that can be streamlined. With the process broken down into the various steps you can see which steps can either be combined into one work station, or can altogether be removed from the process. For example, a lawyer’s firm may send several emails to a client with information in them regarding their services and fees from the relevant departments, looking at the process it could be streamlined into a welcome package all sent from the admin staff instead. This saves time and does not overload the amount of information from different sources for new clients. Happy staff and happy clients.

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(c) McDonald Consulting Group

Overall a Value Stream Map is a beneficial tool for any business when the relevant data is included. It helps to analyse the different processes involved in providing their consumer with a product or service. Perfect for getting the workforce to join in with the planning of processes and identifying any errors within the workflow itself. A simple yet effective tool for lean management in any industry.

The Importance of Relevant Data In A Value Stream Map (2024)
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