The SME's Guide to Automation: Understanding and Applying Key Archetypes
Breaking Down the Barriers to Automation for SMEs
Automation is often seen as the domain of large enterprises, perceived as too complex or costly for smaller businesses to implement. However, as The Manufacturer aptly points out:
“It’s a common misconception that automation is only accessible to large organizations with access to capital and skills.”
The reality?
“This is simply untrue.”
Automation is no longer an exclusive tool for industry giants. Small and medium enterprises (SMEs) are increasingly tapping into its potential, driven by the sheer volume of data now generated in day-to-day operations. As processes grow more intricate and data streams expand, automation is transforming from a luxury into a necessity for businesses of all sizes.
Therefore, where do you start?
The gateway to successful automation lies in crafting the right strategy—one tailored to your organization’s needs, scale, and objectives. This journey often begins by identifying which processes offer the highest return on automation investment. Yet, a deeper level of insight can be unlocked by understanding the archetypes of automation—the foundational models that dictate how automation systems are structured and deployed.
Understanding the Archetypes of Automation
At first glance, automation can appear complex and unwieldy, but breaking it down into core archetypes makes the path clearer. These archetypes serve as blueprints, offering different approaches depending on the size, structure, and goals of an organization.
According to McKinsey, the primary archetypes of automation are:
● Centralized Automation
● Hybrid Automation
● Decentralized Automation
1. Centralized Automation:
As the name suggests, this model consolidates automation within a single point of control. Imagine an entire operation funneled through one intelligent command center. McKinsey describes it as “a single intelligent landing area.” This structure works well for organizations seeking streamlined oversight, uniformity, and reduced redundancy across processes. It’s particularly beneficial in environments where consistency and tightly managed data flows are crucial, such as manufacturing or logistics.
2. Hybrid Automation:
Hybrid automation strikes a balance. It organizes data and platforms by domains—essentially grouping similar processes while maintaining a level of central oversight. While domains operate independently, they report back to a centralized management system, ensuring cohesive governance. This model is ideal for businesses with diverse operations that need both autonomy and interconnectedness, such as retail chains or healthcare networks.
3. Decentralized Automation:
In contrast, decentralized automation distributes control across various silos, allowing individual departments or units to manage their own automated systems. This approach offers flexibility and specialization but can introduce complexities in maintaining communication between silos. Industries with highly specialized teams, such as tech development or pharmaceuticals, often find decentralized automation advantageous for fostering innovation within independent groups.
Choosing the Right Path
Each archetype offers distinct benefits and is best suited for particular industries and operational goals. Selecting the appropriate model hinges on your organization's size, level of data integration, and desired autonomy across business units.
For SMEs just beginning their automation journey, hybrid approaches often provide a practical middle ground—enabling scalability while maintaining manageable oversight. Larger enterprises or those with uniform workflows may gravitate toward centralized models for their simplicity and efficiency.
Ultimately, the key to successful automation lies in aligning your chosen archetype with your long-term vision. By doing so, businesses can unlock greater efficiency, reduce operational costs, and position themselves to thrive in an increasingly automated world.
Sources:
● “Debunking automation myths in manufacturing” - The Manufacturer
https://www.themanufacturer.com/articles/debunking-automation-myths-in-manufacturing/
● “The Automated Factory Ushers in a New Era of Manufacturing” - Eric J. Halvorson, Automation World
● “Scaling Automation: Two Proven Paths to Success” - Ben Armstrong and Benjamin Berkowitz, MIT Sloan Management Review
https://sloanreview.mit.edu/article/scaling-automation-two-proven-paths-to-success/
● “Revisiting data architecture for next-gen data products” - Aziz Shaikh, Henning Soller, Margarita Młodziejewska and Mitch Gibbs, McKinsey