Digital transformation (DX) is in the air. Discussions abound about how businesses are modernizing by replacing analog processes and siloed, legacy, on-premises technology with integrated, digital, cloud-based solutions. These discussions have intensified over the last year as businesses have been forced to adapt to an ever-evolving “new normal”.
If you’re a small- to midsize-enterprise in the consumer packaged good (CPG) space, you may think that the arguments to modernize your IT systems are compelling, but the prospect of doing it is daunting. It can be hard to know where to start, especially if your business (like many others) has multiple priorities that are not always in perfect alignment. To draw on a well-known proverb, DX is akin to standing in front of an elephant you want to eat and not knowing where to start—only in this case it’s where to start digitizing instead of digesting.
The pandemic has been a driver of DX
The COVID-19 pandemic has accelerated the DX process in CPG as well as other industries. For one thing, there has been a seismic shift toward digital engagement, as a report by McKinsey explains. The partial or total shut-down of traditional channels such as bricks and mortar storefronts and field teams has fostered a rapid acceleration of ecommerce, digitally enabled delivery systems and AI-powered customer service. In 2020 these were all leading use cases for DX.
Similarly, the transformation of front and back offices with cloud-based business apps has sped up as workers have gone remote and IT departments have been tasked with ensuring that communication, collaboration, productivity and security don’t suffer as a result.
While many CPG businesses have made significant inroads in their DX journey, the progress hasn’t been uniform across all areas of the enterprise. A recent study by GE Digital finds that CPG is lagging other industries in DX, and a lack of data management capabilities across their operations is a key factor holding businesses back. Making these capabilities enterprise-wide should be a top business priority.
To realize the benefits of DX, you need to approach it strategically and consider all areas of your business; exactly where and how you invest will depend on your business objectives, such as increasing workforce productivity, driving operational efficiency or improving customer experience.
A digital strategy that leaves in place legacy systems that operate in silos is only a partial strategy, and one that is less likely to succeed—no matter how you’re measuring success. The goal of a comprehensive DX strategy should be expanding across all functional areas, ensuring your operational data is captured and transformed into insights and analytics that provide a 360-degree view of the business.
Returning to our governing metaphor for a moment, your elephant needs more than a digital trunk and tail.
The case for digitizing your manufacturing processes
As a CPG manufacturer, you need to ensure you’re digitizing your production lines and the planning, supervisory and management systems that feed them. Why? For one thing, it’s simply the best way to analyze production, find opportunities to optimize it and test the effects of specific changes.
As a general rule, anything that can be digitized can be improved using computer programming and data science techniques to identify underperformance and simulate the effects of change. It’s much less costly and more agile to simulate changes to production processes in a digital environment, where you can effectively test as many variables as you wish and optimize a process before implementing the solution in a real production environment.
Beyond the ability to simulate, test and optimize changes, there are many potential advantages to investing in smart manufacturing, including:
- better inventory management
- better quality management
- better reporting and insights
- enhanced ability to respond to issues
- more effective production planning and scheduling
The fundamental promise of investing in DX is compelling, but many businesses are finding it difficult to get started.
So if you’re struggling with moving forward, you’re not alone. If you’re not sure how best to capitalize on the valuable data and insights you’re already capturing or could be capturing, here are some important considerations to get you started on your journey.
Build a new home for your data
One way to capture data from your current operations systems so you can achieve better and faster reporting and analytics is by building a data warehouse. With this approach, you can put your focus on data engineering rather than ripping out and replacing legacy systems with new ones. Data engineering allows you to fix existing operational challenges, including insufficient business data, without having to change your systems wholesale.
Good data engineering acts like digital glue that connects systems and data sets, extending the lifetime of legacy technologies and creating added value for your organization. It can be a good first step for organizations that haven’t budgeted for a wholesale transformation of their production systems and/or don’t have a comprehensive technology roadmap but do need better analytics to inform business decisions.
Simplify and streamline your analytics
Building a data warehouse infrastructure that automatically captures and archives data from across your organization opens up exciting new possibilities for reporting, including customizable dashboards that display the leading indicators executives need to manage operations and the real-time reports that plant workers use to respond to issues in real time.
When rethinking your business reporting, one of your goals should be simplification. Chances are you’re already generating too many reports across the organization, and few (possibly none) are providing you with all the information you would ideally like to see. As the methods of collecting data increase (as in more sensors, more databases, more spreadsheets) so does the likelihood of data fragmentation, And if you’re building reports manually (as in cutting and pasting data from multiple sources into report documents), you’re adding another level of complexity as well as increasing the possibility of errors.
With a centralized, automated data infrastructure, the right statistical measurement and a modern business intelligence (BI) platform, you can build the views of your operations that you actually need.
Assess your current state of automation
Are you at a point where you need to drive more automation in your production processes? Arguably, smart automation should always be part of your strategy to increase productivity and efficiency, and if you haven’t formulated a plan you’re putting yourself at a competitive disadvantage. When undertaking this analysis, It can help to think about your “automation pyramid”, which consists of five levels:
- Field level: sensors capturing data on the plant floor
- Control level: programmable logic controller (PLC) controlling specific devices and sensors on the plant floor
- Supervisory level: supervisory control and data acquisition (SCADA) system monitoring and controlling multiple production systems from one location
- Planning level: manufacturing execution system (MES) managing the entire manufacturing process
- Management level: enterprise resource planning (ERP) system providing executives with view of whole organization