Overcoming Digital Paralysis in Manufacturing: Strategies for Cybersecurity and Supply Chain Resilience

Nearly 40% of food and beverage companies identified cybersecurity as their biggest business challenge, with recent attacks on major companies like Dole, Sysco and Mondelez demonstrating how cyber incidents can disrupt production lines and create costly supply chain delays.
Companies are shifting focus from cost-driven decisions to prioritizing agility, quality and reduced carbon footprints through localization strategies like friendshoring and reshoring with the help of AI-driven demand planning and scenario modeling.
Manufacturers should prioritize secure cloud computing with single-tenant architectures to centralize data management while providing for consistent security policies and built-in disaster recovery.

In 2025, industry finds itself at a crucial crossroads. While manufacturers understand that digital investments are now a prerequisite for business survival, the abundance of many seemingly perfect options makes the decision-making process overwhelming. This has led to what is referred to as “option paralysis.” As a result, manufacturers are falling behind.

Recent IFS research, conducted with Censuswide, surveyed more than 800 global manufacturing leaders, largely in the food and beverage industry, across the U.K., North America, Europe, the Middle East, South and East Asia, and Australia. The report found that fewer than 10% of respondents qualified as digital leaders, despite all the respondents acknowledging that their business cannot survive without the supporting technology in place. Most surprisingly, nearly two-thirds of respondents considered themselves as “laggards,” who are falling dangerously behind and have stalled at the early stages of digital transformation with no firm plans in place.

Where to start with digital transformation

Technology has the potential to improve production optimization, energy management/waste management and design and development, but only if companies can successfully integrate new technologies into their existing ecosystem. So how can food and beverage manufacturers turn the tide? By focusing on specific areas that have the biggest potential to negatively impact their operations — supply chain vulnerabilities.

AI-driven demand planning helps manufacturers move beyond historical averages by incorporating real-time data from multiple sources — like weather, promotions, market trend or tariff updates.

Maggie Slowik, global industry director for manufacturing at IFS.

Cyberattacks wreak havoc on supply chains

Our research showed that cybersecurity was considered the top business challenge for 36.5% of food and beverage respondents. That’s no surprise considering that companies such as Dole, Sysco, and Mondelez are three big name food and beverage companies that experienced cyber incidents recently.

Any downtime on production lines caused by cyberattacks can lead to a chain reaction of delays, which puts strain on organizations and costs them already limited time and resources. The ransomware attack on Dole, for example, impacted shipments to grocery stores with costly repercussions.

According to the research, 20.6% of food and beverage companies plan to prioritize improving cybersecurity in the next 2-3 years. Interconnected systems and reliance on digital tools increase a company’s vulnerability to attacks. This is why it is important for companies to invest in secure technologies, such as cloud computing, which most manufacturing executives are prioritizing as the cornerstone of their digital transformation efforts.

Yet it’s equally important to have security measures built into the cloud software architecture. A single-tenant cloud architecture, for example, ensures companies can benefit from greater management control and higher levels of isolation — perks they would not be able to receive from a multi-tenant hosting architecture. This removal of access points allows companies to dramatically reduce the risk of data inadvertently falling into unauthorized hands. In the event of a cloud neighbor becoming compromised by a cyberattack, a single-tenant architecture can ensure that a company remains isolated from the threat and their data is left intact.

This applies to the use of cloud computing for data analysis and for use of SaaS (software-as-a-service). For example, centralizing data in the cloud, rather than relying on fragmented, on-premises systems, makes it easier to apply consistent security policies, monitor access and respond to threats. This is especially valuable for manufacturers managing distributed operations and complex supply chains. At the same time, modern production and enterprise apps delivered via SaaS (such as ERP, MES or asset management systems) benefit from frequent updates, built-in security protocols and strong disaster recovery options that many manufacturers would struggle to maintain with their own infrastructure.

Digital tools such as AI-driven data pattern recognition allow food and beverage manufacturers greater opportunities to redesign their supply chain network, implement more rigorous risk assessment tools such as what-if planning scenarios for material and operational resources, and drive better supplier relationships and collaboration.

It’s time to go local

With our research indicating that cost is no longer the prime driver behind supply chain decisions, this leaves manufacturers to achieve a balance among factors such as product lead time, quality and reduced carbon footprints. This is leading manufacturers to assess geographic strategies to optimize supply chain resilience, opting for closer or politically stable sourcing destinations. Localization strategies such as friendshoring and reshoring can provide greater quality control, reduce environmental impacts, improve speed to market and offer better IP protection.

According to our research, improving agility and flexibility of operations is now a top priority for 23.8% of food and beverage companies in the next few years — and technology can make this a reality. Digital tools such as AI-driven data pattern recognition allow food and beverage manufacturers greater opportunities to redesign their supply chain network, implement more rigorous risk assessment tools such as what-if planning scenarios for material and operational resources, and drive better supplier relationships and collaboration.

For example, AI-driven demand planning helps manufacturers move beyond historical averages by incorporating real-time data from multiple sources — like weather, promotions, market trend or tariff updates. This leads to more accurate forecasts and better alignment between production, inventory and customer demand.

IFS’s AI-embedded demand planning capabilities, for example, allows manufacturers to factor in carbon footprint as part of their demand planning capabilities. Users can query potential outcomes, such as: Is it more environmentally friendly to produce glass bottles rather than plastic ones?

With these kinds of what-if scenario planning capabilities, manufacturers can use simulations to model the impact of various risks, such as a supplier delays, price spikes or production disruptions. This helps companies identify the most resilient options before making changes and is especially critical in food and beverage where shelf life, regulatory compliance and seasonal demand patterns all add complexity.

Maggie Slowik is global industry director for manufacturing at IFS.