Key to optimising value from decarbonisation is making it part of everything – from the products made to the processes employed, as well as management practices and sourcing strategies.
Paul Cooper is a Director and Industrial Manufacturing sector specialist at Vendigital. He recently shared his insights with Board Agenda.
Strategic decision-making has never been more complex or challenging than it is today, owing to the ever-changing range of macro- and micro-level considerations that must be taken into account on a daily basis.
To succeed in driving growth in a downturn, however, business leaders know they must find a way to cut through this web of complexity and adopt an agile, data-driven decision-making model that is capable of delivering value for the medium to long term—but how?
Research published by Vendigital has found that 84% of C-suite executives at UK-based companies believe it has become more difficult to make the right decisions at the right time, due to the need to weigh up complex considerations.
In some cases, this increased complexity is due to macro-level considerations, such as high inflation and rising interest rates, along with ongoing uncertainty surrounding the war in Ukraine. In other cases, the complexity is rooted in more specific, micro-level issues, such as material or labour shortages, or other market constraints.
For example, some manufacturers are being affected by supply-side disruption caused by the global semiconductor shortage, or the lack of staple goods coming out of Ukraine, such as grain and sunflower oil.
In other sectors, labour shortages and post-Covid hybrid working expectations are limiting production and outputs. Some boards are exploring ways to circumvent these operational and labour issues by increasing automation, but knowing how much and where to invest can be a difficult call, particularly in a climate of demand uncertainty.
The most challenging decisions
According to the research, the top three most challenging decisions for boards in the current climate relate to pricing, cost-cutting and operations. For some businesses, pricing decisions have become a weekly or even daily consideration, due to significant cost volatility and high inflation.
Boards have to decide whether or not to pass on cost increases to stay profitable, or, in some instances, to even choose to cut prices to drive market share at a critical point in the product’s lifecycle.
Cost-cutting opportunities can be challenging to unearth and real-time data often holds the key, by shedding light on where there might be opportunities to right-size the supply chain or minimise stock and lead times, for example. It is therefore important that boards find a way of streamlining costs without sacrificing quality and customer service.
Unlike some of the other complex decisions that boards have to take every day, operational decisions can be more costly and time-consuming to implement. They could be inspired by macro-level concerns, such as heightened geopolitical risk in a specific region of the world, but they are ultimately designed to deliver value over time.
For example, reconfiguring supply chains to reduce reliance on suppliers in China could present value-driving opportunities at the same time as de-risking supply lines and improving operational resilience. Equally, trading with suppliers in less developed countries, such as Mexico or India, could support a company’s ESG performance and play a role in attracting and retaining talented workers in the future.
Adopting an agile approach
To respond effectively to fast-changing customer demand, rapid decision-making is vital, and this can only be achieved by cutting through complexity and eliminating operational “noise”. Access to accurate, real-time data is key, otherwise businesses are effectively flying blind. To achieve real-time data visibility, the supply chain must be fully integrated, from the customer through to the supplier, so it can respond to demand signals and implement fast feedback loops in an agile way.
A number of emerging software tools can help to improve the accuracy of demand forecasting. For example, demand sensing uses leading indicators and actual data direct from point-of-sale and other customer touch points to get closer to the customer and detect changes as they happen. With more accurate, real-time information about customer demand, businesses can plan in activity in areas such as production and logistics, whilst at the same time minimising the cost of inventory.
In a more complex and uncertain world, boards need to adopt a data-driven decision-making model that gives them the insight and flexibility needed to make the right decisions at the right time. This will enable them to cut through the web of complexity and allow them to focus on realising value for the medium and long term.
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