R.L. Schreiber, Inc. Flavor Purveyors

From Business Goals to Technology Decisions

Before a technology strategy can be properly aligned, IT leaders must first understand the organization’s overall strategic goals and principal objectives. This includes knowing the company’s business growth model and direction. Is the organization planning organic growth, expansion into new markets, or mergers and acquisitions? Are there major operational changes or challenges on the horizon? Will there be shifts in the product portfolio or sales funnels in the near future? Once the organization’s strategic plans are clearly outlined, IT leaders can shape a technology strategy that directly supports those business goals and customer demands. When it comes to food manufacturing, industry trends are constantly shifting and evolving, so it is important to tailor technology strategies to also adapt to potentially changing industry demands and regulatory requirements as well.

“AI will allow the entire industry to make tremendous leaps in productivity over the next several years, allowing human capital to focus on what is most important to the business.”

Strong IT governance is what makes that adaptability possible. While the role IT plays may differ slightly between different types of manufacturers, the overall objectives are the same. Improve efficiency and uptime, strengthen security and compliance, align technology with business strategy, and reduce risk wherever possible. There needs to be a strong ownership of systems and data and a well-defined decision-making authority for technology investments and management. Every "system of record" needs standardization across the organization such as ERP ,WMS, CRM, and MES platforms.  Data needs to flow cleanly, efficiently, securely, and accurately through each system. IT initiatives must also be based on business impact, and not urgency alone. Most importantly, cybersecurity and business continuity need to be the backbone of every system that's implemented within the organization. While IT governance is primarily administered and maintained by IT, it requires the active participation of all departments within an organization to be meaningful and effective. 

Real-Time Visibility and the Case for Clean, Consistent Data

One of the greatest challenges of getting technology to align with supply chain, production, and day-to-day operational performance are challenges with fragmented or incomplete data.  More often than not, this is the crux of most identifiable operational problems. It is imperative to ensure all departments are working off the same data. Using an ERP or some other equivalent system of record facilitates this.  Data integrity and consistency are critical towards achieving smooth, reliable, and predictable outcomes. This helps avoid stockouts, excess inventory, manufacturing miscues, and allows a faster nimbler response to customer demand changes. Creating real-time visibility into what is currently happening across all departments is incredibly advantageous. This visibility improves coordination, execution times, maximizes cohesion, and generates consistency while at the same time avoiding unnecessary risk and downtime. Using AI can often help by performing more repetitive, analytical, or predictive tasks reliably such as having it process large amounts of data to quickly identify data inconsistencies, discrepancies, issues, patterns, or unique opportunities that might normally be overlooked by humans. 

Leading Digital Change and What Comes Next

Managing digital change successfully depends on more that technology, it depends on people. Delegation, participation, engagement, and contribution is a must when working with cross-functional teams towards managing digital change. IT cannot be the sole champion behind it.  Inputs must come from stakeholders within other departments who help to clearly define business goals and objectives. The culture of the organization must emphasize that everyone has a role to play when managing digital change. IT is the key technology enabler, but experience has taught that the most successful outcomes are tied directly to tightly knit cross-functional teams where every active participant has made key contributions to the project and has a vested interest in seeing it through successful completion. 

The culture of shared ownership becomes even more critical as technology continues to evolve. Particularly AI will have a profound impact on the food and beverage industry over the next several years. In many ways, it's starting to occur already. There are so many business use cases where AI provides significant advantages to food and beverage manufacturers who wish to reduce repetitive tasks, provide faster and deeper data analysis, increase speed, quality, and consistency across supply chain and operations, and free employees to focus on higher-value activities. Already the industry is seeing a strong emergence of industry-tailored AI tools such as food and beverage focused chatbots, prebuilt or custom agentic orchestrations "AI workers," and AI generative tools that allow companies to leverage their existing data in ways they never thought possible or could never achieve in the past using traditional methods. This is only the beginning for AI. It is anticipated that AI will allow the entire industry to make tremendous leaps in productivity over the next several years, allowing human capital to focus on what is most important to the business. The future is very exciting and moving forward very rapidly for the food and beverage industry.