With defence spending increasing and civil aviation passenger numbers predicted to rise, could this be the year that they put their ‘factory of the future’ strategies to the test?
We work with organisations to help them understand their manufacturing and other processes, analyse how these impact their business and align with their strategies. Through the systematic removal of elements in your manufacturing or other processes that do not add value, our experienced team can help streamline your operations to improve efficiency and reduce costs.
We leverage a step-by-step lean methodology that aims to remove any activity that does not add value from the client’s manufacturing or other processes. Known as non-value-adds (NVA), these elements add time and/or cost to the manufacturing process without providing any benefit. Although approaches vary, the principal mechanism applied to solve these challenges and drive improved efficiency is the DMAIC improvement cycle – Define, Measure, Analyse, Improve and Control.
Define (Process Mapping)
Before we can adapt any processes, the critical first step is to define and understand the process steps from an agreed start and endpoint. Processes can range from high to granular level detail and by guiding the client in defining these processes, we can then identify the opportunities for improvement.
Measuring the baseline
By harnessing data insights we can determine how long a process takes to complete and, as a result, understand which are the most time-consuming and cost intensive.
Analysing the process
With our strategic expertise, we have a variety of tools and techniques available to analyse the processes, understand which areas you wish to target and where we believe improvements need to be made.
Improving the process
Working in close collaboration with our clients, adopting a creative approach and applying a number of proven process improvement techniques, such as the single item flow, Kanban, automation, predictive maintenance and Single Minute Exchange of Dies, we can develop methods to remove time-consuming processes and NVAs, or at least cut down lead times, and thereby reduce operational costs.
Controlling the improvement
For sustained improvement, the measures put in place must avoid a return to previous performance. We work with organisations to help create and develop control measures that are either built into the process itself or set key performance indicators to monitor ongoing performance. Utilising visual management tools, such as dashboards or manufacturing boards, KPIs should include leading (what could happen) and lagging (what has happened) performance indicators and must be aligned with corporate operational strategies.
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The benefits of best practice
By partnering with key relevant members within an organisation, we can help deliver improved efficiencies of operational processes, bringing about a reduction levels of non-conformance, streamlining non-standard processes, driving significant savings in operational costs and increasing cash flow.
Improved efficiencies of current operations
For any business in today’s competitive environment, optimising operational efficiencies and reducing costs allows for better upscaling and business resilience.
Increased cost-efficiency of manufacture
Reducing operational costs and building continuous process improvement enables organisations to gain a competitive advantage and improve cash flow.
Reduced levels of non-conformance
By removing high levels of non-conformance through clearly defined processes and KPIs, improvement will be sustained and performance non-reversible.
Standardising operational processes not only streamlines the process and brings them in line with operational strategies but also enables ongoing process improvement.
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We share industry insights across aspects of EV Supply Chain, Battery Manufacturing and Circular economy including what businesses can do to create certainty around business growth.
Product and pricing decisions are key to survival. But how can a complex business make these decisions amidst so much uncertainty? The answer lies in data understanding.