-Adam Sharman, Senior Partner, Dsifer
In New Zealand these cost pressures are compounded by high shipping costs and unfavourable exchange rates that impact New Zealand manufacturers’ price competitiveness and/or margins. All of which is contributing to a contracting in manufacturing performance in New Zealand and most of the world.
In challenging times, most organisations look to reduce production costs and non-essential spending. However, too often we see organisations making knee-jerk approaches to cost cutting, resulting in short-term decisions that constrain their ability to improve or accelerate when the economic environment improves.
Whilst it may seem paradoxical, challenging cost environments can be the foundation of future growth, if managed through an evidence-based, future-focused approach.
In this article we will explore three key ways a data-driven approach to managing through challenging economic environments can help balance the need for short-term cost reduction with long-term performance.
Understand the true drivers of production costs
Most organisations already collect a huge amount of data at multiple stages of the manufacturing process. However, a significant proportion do not use this data to inform process efficiency, asset optimisation and waste reduction.
A data analytics approach that identifies trends in process, machine and people data can identify correlations between multiple factors that explain the drivers of production efficiency, bottlenecks or opportunities to optimise.
Having identified these drivers, scenario modelling can then be used to play out different combinations of variables identifying the optimal combination.
For example, identifying the root cause of systemic asset failures, and modelling out an optimal maintenance schedule to mitigate future unplanned downtime.
Evaluate the true impact of cost reduction decisions
Building on the ability to understand the drivers of production costs, a data-driven, evidence-based approach allows for the interrogation of cost reduction strategies to understand their true impact on production and prioritise them accordingly.
Too often, when facing challenging economic conditions, we see organisations prioritise short-term cost cutting measures that actually result in unintended longer-term costs or jeopardise strategic agility. For example, it is tempting to reduce headcount and the associated wage bill through redundancy or natural attrition.
However, data analytics have frequently shown a significant down-side to this approach resulting from higher overtime bills, not to mention the increased likelihood of absenteeism, quality failure and injury rates that occur as workers fatigue.
By taking a holistic, data-ever, data analytics have frequently shown a significant down-side to this approach resulting from higher overtime bills, not to mention the increased likelihood of absenteeism, quality failure and injury rates that occur as workers fatigue.driven approach, cost reduction measures are able to be evaluated and prioritised based on their overall cost impact on the organisation, including their potential down-side impacts.
Improve forecast accuracy to inform business planning
Data analytics can significantly enhance forecasting accuracy through combining historical patterns and trends with external data sources such as weather forecasts, market forecasts and major event calendars, to create predictive analytics algorithms that can forecast future trends with greater precision.
These predictive algorithms can be further refined through scenario modelling and machine learning to enhance their predictive power. Greater forecast accuracy enables businesses to reduce costs through, for example, optimised inventory holdings based on projected customer demand, optimised product margin based on forecast market pricing and optimised workforce planning to match forecast production.
How organisations respond to challenging environments sets the foundation from which they are able to recover, accelerate or thrive as the headwinds reduce.
Organisations that take a knee-jerk approach to cost cutting as the economic indicators turn downwards often find themselves behind their competitors as the market picks up and they are not able to respond to increased or changing demand.
Using data that is already being collected, organisations are able to take a data-driven approach to cost reduction based on informed decision making that balances the need to increase efficiency, reduce waste and reduce costs whilst not jeopardising future agility and performance.