Manufacturers are drowning in data — they need a lifeline
By Brett Hansen, Chief Growth Officer at Semarchy
Manufacturing enterprises lead all others in data generation. According to AWS, manufacturing companies generate more than 1,800 petabytes of data yearly — twice as much as the second most data-intensive industry.
Brett Hansen
Data proliferation creates significant challenges for manufacturing leaders. Among them is the difficulty of efficiently managing and understanding data from disparate, often incompatible sources. Without a centralized data repository, leaders lack an accurate overview of their operations, so informed decision-making becomes incredibly challenging.
These organizational hurdles will become increasingly complex and pressing as the Industrial Internet of Things (IIOT) expands. Statista predicts the global IIOT will be worth over $525 billion by 2028, up from $325.80 billion in 2024. Meanwhile, the average data scientist spends 80% of their time simply preparing data for analysis. That leaves sparse time to actually analyze and glean insights from data.
It’s high time for manufacturing leaders to address their organization’s data problem. In fact, many leaders are currently reassessing their supply chains to build more efficient and robust operations in the wake of COVID-19 — making now the perfect time to enhance your data strategy.
Answering the industry’s top concerns with data
According to Rootstock, manufacturing leaders believe the following forces will significantly impact economic operations in 2024:
- Suppliers becoming more unreliable/unpredictable (35%).
- Transportation and logistics becoming more unreliable/unpredictable (33%).
- Increased demand (23%).
- Factories needing to expand (21%).
- Staffing issues and hiring freezes (21%).
Proper data management can mitigate the adverse effects of all the above.
Leading data systems provide insights into transportation trends and suggest advantageous supplier contracts by maintaining access to high-quality data about previous supplier relationships. Furthermore, relying on machine learning (ML), these systems can communicate opportunities to meet increased demand by scaling operations up or down. Finally, insights from data systems drive a more efficient staffing strategy because they ingest previous staffing patterns and understand productivity goals.
However, without a robust data management strategy, these critical insights remain locked.
Revitalizing the data status quo
Leaders must challenge the data-manufacturing status quo by enacting the following changes:
- Implement a data standardization and cleansing program. Manufacturing data comes in many shapes and sizes, including data about suppliers, customers and products. The first step to a revitalized data program? Standardize these data formats across all departments and cleanse the data to remove duplicates, errors and inconsistencies. Doing so is crucial to ensuring that organizational data is accurate and reliable.
- Automate data collection and processing. Once they’ve organized archival data, leaders must ensure continuous data hygiene. By adopting automation tools to collect and process data, leaders can reduce the time and effort required for data entry. In the process, they’ll improve accuracy and free up resources for more analytical, high-value tasks.
- Invest in training and skill development. Data organization protocols may start at the top, but they should never remain there indefinitely. All stakeholders must understand the benefits of good data management practices. Equip your team with the necessary skills and knowledge to handle data effectively. This should include training in data analysis and best practices for data management.
- Adopt a master data management (MDM) system. MDM systems provide a central repository for all critical data, ensuring consistency, accuracy and accessibility. This approach helps eliminate data silos, standardize data formats and improve overall data quality. MDMs are especially crucial for mid and large-scale enterprises looking to activate new market opportunities.
- Explore advanced technologies like AI and ML. Almost three-quarters (73%) of business leaders feel pressure to implement AI solutions — and soon. But AI and ML-backed technologies are counter-productive to adopt without first getting a handle on your data systems. As such, ensure this is the final step of your data strategy.
Good data pays dividends
A revitalized data management strategy unlocks several opportunities for manufacturing organizations. Leaders can rely on accurate data to enhance visibility and traceability across their supply chain, assuaging concerns about supplier risk. Internally, good data provides insights that streamline operations and significantly reduce lead times. These benefits create cost savings, ultimately leading to improved organizational decision-making.
Manufacturing leaders can no longer settle for less when it comes to data. Leaders who prioritize data quality and management in 2024 will unlock immense competitive advantages, especially as MDM capabilities expand and the role of data becomes even more integral to business continuity.
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About the Author
Brett Hansen is responsible for Go-to-Market operations, including marketing, business development, and alliances and partnerships.
Before joining Semarchy, he was the CMO at Logi Analytics, which was acquired by Insight Software. He spent eleven years at Dell as an executive leading software product and GTM in Dell Client Group, and prior was with IBM in various marketing and channel leadership positions.
