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.
Nick Harrison is a Partner and Head of Consulting at Vendigital. He recently shared his insights with Business Reporter.
Some Boards are feeling the pressure when it comes to making the right decisions and answering to diverse stakeholders, due to gaps in their business data. Recent research conducted by management consultancy firm, Vendigital, has shed light on the types of decisions that C-suite executives expect to find the most challenging in the year ahead, but how could closing the data gap help?
Not only have businesses been forced to contend with Covid-19, supply chain challenges, rising inflation and the war in Ukraine, but the recent energy crisis has also had a material impact on revenue and profit; particularly for energy-intensive manufacturers.
As Boards look to the future, these financial pressures will be compounded by the push to decarbonise and implement ESG strategies. The only way that businesses will be able to rise to these challenges, while simultaneously creating the lean, green supply chains of the future, is through the use of insightful and accurate data.
Filling data gaps will help to drive business performance by assisting decision making, clarifying business purpose and strategy, and cutting through complexity.
Effective decision making relies on more than keeping track of revenue and profit. Boards need to take a holistic approach to business management, particularly as ESG demands increase. For example, procurement teams will naturally seek to purchase components or raw materials at the lowest cost. However, by viewing activity through a lens of sustainability, it may become clear that the lowest-cost supplier has the highest carbon footprint, due to production methods or shipping distances.
While switching supplier may reduce carbon emissions, it could drive-up costs. For the Board to understand the implications of making such a change, accurate and reliable data is key, and will enable them to model scenarios and reach a consensus on the best course of action.
AI and machine learning are fundamental to the development of dynamic, decision-making models, and digital twins can be particularly effective in the manufacturing sector. These models allow the business to input a task, such as the production and shipping of a specific component, in order to assess its impact on the overall production process, commercially and environmentally. Different scenarios can then be produced based on variables such as reducing carbon, cutting costs or nearshoring.
The development of a bespoke decision-making model will allow Boards to digitally test a proposed change before it is implemented or cap ex allocated, minimising disruption for both the business and its supply chain. For manufacturers, this method of filling data gaps can help to ensure that production capacity is right-sized from the start and avoid costly mistakes.
Having reliable data is the only way to identify and remove root cause issues, which could blindside decision makers. However, this data must be insightful and easy to use. Companies that keep their departmental data in separate silos may face problems when attempting to gain a holistic overview of operations, as the different data silos could be in different ‘languages’ and use different metrics.
Investing resource to ensure that all data across a business is aligned could seem a daunting task, but it is the only way to produce meaningful and reliable insights.
For a business starting out on a data journey, the most important step is to understand its goals and objectives and seek professional guidance where appropriate.
With a specific goal in mind, for example, reducing carbon emissions across a global supply chain, board-level decision makers can utilise data to understand the current situation. They can then work backwards, using AI and digital twins to run different scenarios and create a strategy based on fact rather than predictions. Equally, benchmarking plans against others in the industry could help businesses to achieve their ESG and other performance-related goals.
With net-zero targets nearing, collaboration and learning cross-industry lessons will become increasingly essential, particularly as businesses start to realise the potential of AI-based systems and machine learning.
Ultimately, Boards need to understand what is within their control, and what is not, and data is key to unlocking this insight. While it might not be possible to change some of the macro-level challenges that businesses face, closing the data gap will give them greater control when it comes to delivery.
Those Boards that utilise data successfully today, will be most likely to become leaders in their markets tomorrow.
Share this insight
Share this insight
Implementing a data strategy is critical, but there is little point unless you are serious about protecting data integrity at every turn.
As the market for used electric vehicles starts to mature, the condition of the battery that accounts for much of a car’s value is becoming an important factor in buying decisions.