Globally, the use of data is growing — and in the past two years, the pandemic has been the main driver behind worldwide data growth, including increased internet access and a new way of working. The pandemic also opened the door for new competitors, an increased need for predictive data, and a need for new customer-centric business intelligence models.
Data plays a huge role in the ability to manufacture. Data enables manufacturing companies to draw powerful insights, and create transformative experiences for customers and business growth. It is used to drive productivity, and new customer experiences, and to create a positive societal and environmental impact. Many manufacturers just aren’t maximizing its value and missing out on the unmatched efficiencies it provides. Ultimately what should matter most for business is not the volume of data but, rather, knowing how to use it.
Collecting data for effective usage with business intelligence
Many manufacturing companies still rely on Excel for all sorts of tasks including scheduling, inventory management, and data analysis. However, today’s manufacturers need a more robust, effective, connected, and specialized tool to run their businesses.
Manufacturers need to rethink how they collect data, store it and manage it so it works for them. A recent report by SYSPRO reveals that while at least 47 percent of businesses invested in sensors, IoT, or IIoT, the main solution for manufacturers and distributors to thrive regardless of foreign conditions is to rethink and realign their supply chain to engineer a bounce-back.
Within the manufacturing industry, the use of sensors, IoT, or IIoT is paramount for collecting essential information. The sensors collect data that is used in various ways including, monitoring the health of a manufacturing machine or how much time it takes to manufacture a product. Data gathered through IoT sensors and control towers also helps create periodic maintenance schedules that have minimum impact on the continuity of production lines. The data is stored in a database managed within the building or in the cloud for processing and analysis.
Unfortunately, many manufacturers are still lagging behind and not leveraging these benefits. The same SYSPRO survey went on to reveal that only 20 percent of businesses had invested in data analytics tools to process and analyze the data that they were collecting, while only 5 percent of companies had investigated AI and ML to draw any long-term benefit from the data collection. Data-driven decision-making should form part of a business’s daily operations.
Using data to prepare for uncertain times with business intelligence
Over the years we’ve noted how times of crisis, whether financial, geopolitical, or weather-related, can affect business performance.
For instance, the recent war between Russia and Ukraine not only affected the petrol and oil prices significantly but the war-imposed constraints on the ability to use Russian transportation infrastructure to support manufacturing in Asia, proving that this crisis requires a particular set of resilience capabilities.
The Ukraine war also has a large impact on car manufacturers in Europe, highlighting the risk associated with the current global supply chain. Even though it is possible to ship some of these items by air, that is significantly more expensive, especially now that airlines need to bypass Russia.
Data can come in and spur decisive and agile predictive insights that can assist with reducing costs associated with such changes. One thing the conflict in Ukraine has demonstrated is that it is imperative for organizations to have in place more resilient supply chains, and this can be easily achieved through drawing such insights from data.
Data-enabled visibility through ERP
Visibility is one of the core pillars of a resilient supply chain—and it should extend to the entire network. The data can also be fed into Machine Learning (ML) and Artificial Intelligence (AI), to flag up potential disruptions and allow the management and mitigation of risk. To get a better grip on where risks lie, implementing “control towers” powered by AI/ML and advanced analytics can provide right-time data visibility, proactive alerts, prescriptive insights, and self-driving execution.
The visualizations available with embedded analytics help understand the trends and forecasts across the business, for operational KPIs or to extend Supply Chain Control Towers, which enable organizations to understand, prioritize and resolve critical issues in real-time.
One of the biggest challenges with data is that it can exist in silos with no strategic framework. The advantage of an ERP system is that it provides the architecture to consolidate data so it can be useful. The value of data comes from the insights it creates, and how it can help to optimize and improve how decisions are made.
Through an ERP system, manufacturers can analyze forecast demand changes, accurately predict production targets and thus easily meet demand levels.
A digital roadmap should form part of any business operations and must be aligned with a business’s changing needs. The best way possible to achieve business intelligence is through an automated enterprise resource planning (ERP) system that can business systems, even more efficient.
While, manufacturing is going through digital transformation, and much of the focus in the future will continue to be to increase the productivity of the shop floor by empowering workers with better tools by ML/AI, there are countless opportunities that lie in embracing the data-fueled innovations of the fourth industrial revolution