Four Digital Efforts Bring Balance To The Mill Products Sector

Jennifer Scholze

Part 3 of the “Intelligent ERP-Driven Industries” series

In capital-intensive, high-volume, commoditized marketplaces, balance is an art and science that must be mastered every day. Excess capacity, volatility in raw materials access and cost, surging energy prices, and tightening regulations – these realities of the mill products industry can potentially throw operations and profitability out of kilter at a moment’s notice.

Digitalization is a two-way debate of opportunities versus disruptive implications, whether your business manufactures iron, steel, aluminum, paper, pulp, packaging, building materials, or textiles. On the one hand, there’s the promise of a nimble and profitable business model running on faster decision-making; an empowered workforce; and improved health, safety, and environmental impacts. At the same time, these gains can be far from equitable against concerns over disappearing traditional roles, compromised data privacy and security, and a growing shortage of relevant digital skills.

It’s becoming increasingly evident that digitalization is something that cannot be avoided by any business. But can mill products businesses gain the delicate balance they need to survive too?

Future-proof your digital journey with automation and intelligence

Working hand in hand, digital innovation services and a next-generation ERP suite deliver a level of automation and intelligence that powers the evolution of business models, operational processes, and workforce skills for years to come. This approach not only allows mill products companies to run better, faster, and simpler, but also builds a connected business and drives continuous growth.

Here are four use cases that can help mill products reap the benefits of digital transformation while mastering the balance needed to respond to a constant wave of external change.

1. Order to cash

In most organizations, the accounts receivable (AR) team goes through a lot of manual effort from the moment they receive an order until the payment is processed. As companies grow their customer base, the AR function needs to handle the increased volume of payments without adding more accountants. At the same time, it needs to keep days sales outstanding in check by ensuring that cash does not sit too long in a customer’s account.

With machine learning, AR teams can be liberated from the daunting task of reconciliation to drive more strategic activities. The technology captures how AR accountants process remittances and adjust their actions to address submissions that use outdated master data or contain incomplete information such as missing invoice reference numbers. Over time, a level of automation is achieved as the machine-learning application constantly fine-tunes its response when handling payments. 

2. Operational contract management

The goal of every contract is to maximize operations and financial performance. Machine learning can help predict the consumption date of each contract to allow your business to engage with suppliers proactively. As a result, you can analyze all attributes of the contracts, including associated purchase orders and vendors. Your organization can leverage dynamic and flexible worklists, access supplier fact sheets, and oversee the contract renewal workflow.

3. Business integrity screening

The detection and prevention of operational anomalies is a proactive approach to protecting your business from fraud risk and insidious loss. Scanning large volumes of data in real time with precision helps identify abnormal activity quickly by using flexible rule sets, Big Data processing, and predictive analytics. Plus, you can monitor key performance indicators and send reports to management to detail how risks are handled and how the process can be improved as cybersecurity breaches become more sophisticated.

4. Predictive maintenance

Tracking the health of your manufacturing machinery and other business assets over time can help eliminate the fluctuating costs, unreliable service, and unplanned downtime commonly experienced with reacting to equipment malfunctions. By applying data science, the Internet of Things (IoT), and machine learning, your maintenance and service efforts can become more predictable and controllable.

For example, you can:

  • Optimize performance availability and production quality: Know the exact moment when your machines should be serviced to extend their usable life. You will not only optimize the ROI of your investment spend, but also save a significant portion of your maintenance budget.
  • Maximize equipment uptime: Predict and resolve performance issues before they become problems that lead to unplanned outages, production delays, and poor-quality products – all of which can adversely impact your bottom line and brand reputation.
  • Take advantage of Industry 4.0 concepts: Leverage real-time analytics to adjust and improve the products you deliver and evolve your business model to respond to market and customer demands.

Seize this digital turning point to differentiate and compete

As the world population gets closer to reaching 9.8 billion by 2050 and the middle class continues to grow in emerging economies, the opportunity for the mill products industry has never been greater. But, at the same time, so is the pressure to quickly deliver products that are high-quality, relevant, and accessible.

These new industry realities are forcing your business and competitors to make dramatic changes.  How will you remain profitable in a marketplace that is highly competitive, continuously evolving, and tremendously crowded? Maybe it’s time to reassess how you can optimize the life of your capital investments and allow every employee to protect your business from global risks and contribute to sustainable growth.

Check out how mill products businesses are putting these four digital capabilities into action. Access our library of keynote and session replays from the Intelligent ERP Industry Virtual Summit to hear from top customers and experts as they discuss how intelligent ERP, industry roadmaps, and implementation can guide your business throughout its digital journey.

About Jennifer Scholze

Jennifer Scholze is the Global Lead for Industry Marketing for the Mill Products and Mining Industries at SAP. She has over 20 years of technology marketing, communications and venture capital experience and lives in the Boston area with her husband and two children.