Industry 4.0 promises many benefits to manufacturing companies, especially in the current environment where the fallout from the pandemic and other concurrent macroeconomic events continue to disrupt supply chains. Labor and material shortages, unpredictable demand, and transportation and logistics challenges are simultaneously challenging organizations’ agility, resilience and market foresight.

However, there are still misconceptions about what Industry 4.0 actually is, and therefore what organizations must implement to take full advantage of what it can offer. Rather than viewing it as a sole data source to drive decision making, consider Industry 4.0 as tools to enable change, improve and stabilize processes, and inform business decision-making by harnessing the powers of interconnectivity, machine learning, automation, and real-time data. 

While the anticipated benefits of Industry 4.0 could be significant in countering the forces of disruption mentioned above, there are often existing issues within organizations that mean the surrounding processes are not ready, established enough or even properly documented in order to digitize them and begin these transformation efforts.

Worse still, these shortcomings are ignored or downplayed, leading to ineffective implementation. For example, the promise of high-resolution, highly accurate data collection in milliseconds rather than days, which can drive pattern recognition and root cause identification will likely be replaced by huge amounts of data that is never synthesized into actionable insights that could drive better business decision-making.

Implementations fall short of their benefits because processes are not properly reflected, exceptions are not accounted for, and the resulting master data is unreliable, and reports are seldom structured or packaged in a meaningful way to enable and drive targeted action.

Brilliant basics will lay the foundations for bigger benefits

The initial steps to successful Industry 4.0 transformation center around truly understanding the business you have around you now. For example, to be able to assess the level of savings a chosen technology will deliver versus true direct labor, your existing talent and future hires must be comprehensively mapped out. Future returns from dynamic demand data can only be crystallized if your automated processes are agile enough to feed the platform from the outset. The list goes on.

Here are five critical foundational actions to take ahead of going all-in on Industry 4.0: 

  • Define processes and improve adherence:
    • Processes that are used to track material flow, labor consumption, and downtimes need to be well defined and adhered to before any digitization can begin
    • Developing value stream maps will help understand bottlenecks and help prioritize the biggest opportunities
  • Invest in your talent:
    • Organizations oftentimes do not invest the right resources or develop an appropriate organizational structure to spearhead the transformation.
    • Hire talent that can train others on digital tools and have the capability to analyze data trends and determine actionable insights
    • Create the right blend of technical, Continuous Improvement (CI) and temporary tech talent to ensuring continuity.
  • Stand-up a change management program / training program:
    • Early on, map key stakeholders and ensure regular 1:1 touchpoints to hear their pain points, perspectives on progress, etc. – constant communication is vital
    • Engage stakeholders in the deeper details of manufacturing processes and get incremental/daily buy-ins versus a big reveal of the results of your work
  • Push for paperless processes everywhere and integrate existing data streams:
    • There is often untapped data sitting either in documents or in disconnected databases (e.g., maintenance work orders) - digitizing and analyzing trends from this information often leads to quick improvement opportunities.
    • Also assess how to unlock other data that can help with quick wins, such as clock-in-clock-out data that could better manage labor hours, machine downtime data etc. and focus on prioritizing efforts to specific segments and 80:20 within these segments to drive early progress.
  • Identify your biggest opportunities - and ensure your 4.0 transformation journey begins by addressing them
    • Crystallizing the problems you need to solve is critical – the solutions may be wildly different from what you holistically anticipated.
    • For example, in our work with a food manufacturing company, paper-based quality assurance processes were identified as preventing real-time intervention and correction to product overweighting. A low-cost, high-impact IoT solution was devised and implemented at four production lines, which quickly addressed this waste issue, generated $4m in annualized savings and sparked a larger organizational digital transformation program.