The past five years have seen the manufacturing sector weather numerous headwinds: economic uncertainty, supply chain disruptions, labor shortages, and more. Rising inflation and the need to meet looming net-zero emissions goals add another dimension of complexity to the situation. Then, there is the necessity to future-proof companies against any challenge that may rise over the horizon in the years to come.
2024 Manufacturing Industry Trends:
- The global manufacturing industry is projected to reach $944.6 billion by 2030.1
- The industry seeks to reorganize and “reshore” its supply chains to ensure future disruptions don’t derail day-to-day operations.2
- Solving the skilled labor shortage remains one of the industry’s primary agendas. Top manufacturers increasingly rely on digital tools to attract talent.3
- Manufacturers prioritize sustainability and carbon neutrality to pursue their Environmental, Social, and Governance (ESG) and net-zero goals.2
- Large-scale manufacturers increasingly adopt Gen AI and data analytics to improve operational efficiency and create new revenue-generating opportunities.3
Planning a more resilient future for the manufacturing industry
Despite numerous setbacks, the manufacturing sector is advancing rapidly to suit the evolving global economic climate, with digitalization playing a significant role. The onus is on top executives, such as chief financial officers (CFOs), to ensure their organizations employ the latest technologies to stay ahead of the competition and capitalize on future opportunities.
When planning for the future, CFOs have their tasks cut out. Apart from devising growth strategies for the near term, they must think ahead to ensure they’re prepared to capitalize on new financial opportunities and be insulated from any undesirable situations. Leveraging big data and advanced analytics can help CFOs in the manufacturing sector uncover deeper financial insights and predictions, allowing them to plan a resilient future for their organizations.
What are advanced analytics, and how can it benefit CFOs?
While many organizations have embraced manufacturing data analytics to some extent, most employ them only to reduce operational costs through predictive maintenance and supply chain management. Only a handful leverage the data gathered for long-term financial planning.
Advanced analytics applies artificial intelligence (AI), machine learning (ML), neural networks, and predictive modeling to extract in-depth intelligence from the datasets generated by an organization’s business operations. Typical data sources in the manufacturing space include sensors on the machinery, equipment performance reports, raw materials procurement data, real-time inventory status, sales statistics, customer information, and historical financial statements.
Over 54% of manufacturers are expected to increase their technology investments in 2024, with business intelligence and data analytics software being the top priority.4
By enabling advanced analytics, the voluminous data generated by a large-scale manufacturer can provide CFOs with invaluable insights to guide their financial planning and analysis (FP&A), forecasting, and resource allocation.
What are the challenges faced by CFOs using outdated FP&A tools?
Integration complexities, sparse datasets, and irregular data updates are some of the challenges that plague the users of last-generation FP&A tools. When it comes to incorporating data analytics in the manufacturing industry, the challenges are further compounded by the sheer diversity of data sources and the gargantuan volumes of data they generate. The lack of AI and customization options adds further constraints in extracting actionable insights for CFOs. Advanced analytics can help CFOs overcome these hurdles.
- CFOs can work with much larger data sets, allowing them to make more informed financial decisions.
- AI can be leveraged to simulate the potential outcomes of many scenarios, which CFOs can analyze and plan for.
- Advanced analytics can help optimize resource and capital allocation across various business functions.
- Implementing predictive models can improve forecast accuracy and enhance decision-making.
- Advanced analytics enables real-time data analysis and custom on-demand visualizations for timely decision-making, which can prove invaluable in a fast-paced industry such as manufacturing.
The insights derived through advanced analytics can help CFOs identify emerging market trends, forecast demand for multiple products, and predict supply chain disruptions. This allows them to determine the appropriate financial strategies and investments and optimize cash flow accordingly.
Easing the CFO’s planning journey
Today’s dynamic business environment requires CFOs to uncover hidden patterns and anticipate future requirements swiftly and accurately. Integrating and analyzing the vast streams of data generated by large-scale manufacturers requires modern tools that are fast, seamless, and possess innovative analytics capabilities.
Tools such as Microsoft’s Dynamics 365 Finance, Oracle Fusion Cloud ERP, and SAP’s S/4HANA Cloud incorporate the latest advancements in AI and natural language processing (NLP) for enhanced data analytics and forecasting capabilities. They can also be tailored for functionalities specific to the manufacturing sector to facilitate demand forecasting, supply chain optimization, inventory management, and regulatory compliance.
With these tools in place, CFOs can navigate the intricacies of the manufacturing landscape with agility and foresight, mitigating risks, unlocking new opportunities, and steering their organizations toward sustained success.
References:
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- Source 4
