Generative Business Process Renovation – We’ve seen this movie before
Some of the hype about Generative AI is well deserved and its impact isn’t over horizon – more like the middle of next week. Fortunately, we have some familiar scenarios to look back on to keep the rug from getting pulled out from under us all together.
A Quick Trip Down Memory Lane
In 1957, the movie Desk Set was a cautionary tale of an efficiency expert and computer specialist (Spencer Tracy) up against the head of the television network’s research department (Katharine Hepburn) in a dystopian story about automation and job displacement. Yes, it’s a romantic comedy.
But it wasn’t until the 1980’s that Business Process Reengineering took hold in the white-collar world. We took a hard look at our core processes and focused on radical redesigns to achieve significant improvements in performance. Cool.
Then came Process Mining in the early 2000s, where we looked at processes in action, quantifying discrete tasks in order to bring about Robotic Process Automation. RPA let us replace repetitive, rule-based chores with bots that could handle drudgery, freeing up humans for higher-level work. Efficiency soared.
And then we hit the Big Time with Digital Transformation. Starting in the mid-2010s, we weren’t just optimizing; we were reinventing based on the reliance of the Internet. We began integrating digital technologies across entire organizations, reshaping operations, business models, and customer interactions.
And now, we face …
The AI Renovation
Generative AI is about innovation on a scale we’ve never seen before. It’s not just doing things faster, better, cheaper, but differently. Much differently.
This is the machine going way past processing data; it’s generating new ideas, new strategies, and new ways of working. It’s a new category. It will spawn entirely new products, new services, and new business models.
Generative AI is democratizing innovation. It’s putting the power to create in the hands of everyone, not just the technologists. Your marketing team can generate new campaign ideas. Your product development can design and test products in ways that were impossible just yesterday. Your HR department can use GenAI to create more effective, personalized employee engagement strategies.
Learning from the Past
When you look at the progression from Business Process Reengineering to Process Mining, Robotic Process Automation, and Digital Transformation, you see a clear trajectory—each step building on the last, each innovation pushing us closer to a more efficient, digital-first world.
Business Process Reengineering taught us the importance of having clear, strategic objectives when redesigning processes.
Process Mining highlighted the value of data-driven insights for understanding and optimizing business processes. It demonstrated the importance of having accurate, real-time data to inform decisions.
Robotic Process Automation taught us the benefits of automating tasks incrementally. Starting with simple, repetitive tasks allowed organizations to gain quick wins and build momentum for more complex automation.
Digital Transformation was all about the need to integrate networked technologies across all aspects of the business, from operations to customer interactions, ensuring that technology adoption was holistic rather than siloed.
Both BPR and Digital Transformation underscored the importance of managing change effectively. Resistance to change can derail even the best-laid plans, making communication, training, and stakeholder engagement critical.
The iterative nature of RPA and the ongoing nature of Digital Transformation revealed that these efforts are never “one-and-done.” Continuous improvement and adaptation are necessary to stay ahead.
Digital Transformation showed the value of collaborating with other organizations, industry groups, and technology providers to build ecosystems to further innovation and share best practices.
Demonstrating tangible value through measurable outcomes was critical in BPR and RPA initiatives. Success was often measured by efficiency gains, cost reductions, and performance improvements.
But Generative AI Renovation is different. While BPR and Digital Transformation focused on optimizing and digitizing what we already do, Generative AI is about creating something entirely new. It’s the difference between upgrading a machine and inventing an entirely new way of manufacturing.
What To Do Now?
Before implementing Generative AI, organizations should define specific objectives, such as improving customer experience, reducing costs, or creating new products. This ensures that AI initiatives align with overall business strategy.
Successful Generative AI applications require robust data collection and analysis. Organizations must invest in high-quality data and analytics infrastructure to ensure that AI models generate valuable and actionable outputs.
Begin with pilot projects that target specific, manageable areas. This approach allows for learning and refinement before scaling AI solutions across the organization.
Generative AI should not be confined to a single department or function. For maximum impact, it should be integrated across the organization, influencing everything from product development to HR practices.
Successful Generative AI implementation requires a strong change management strategy. Leaders must communicate the benefits, provide necessary training, and address concerns to ensure buy-in across the organization.
Implementing this strange, new technology is a journey rather than a destination. Continuous monitoring, learning, and iteration will be essential to adapt to new developments and maximize the benefits of AI.
Organizations should collaborate with AI experts, industry peers, and external partners to leverage collective knowledge, share experiences, and accelerate AI adoption.
Finally, you must develop clear metrics to measure its impact. Not just the classics like increased revenue, lower costs, or improved customer satisfaction, but creativity, brainstorming, and innovation. See my peer-reviewed paper on “Measuring the business value of GenAI” for more.
Change Your Mind and Get in Touch
It’s time to change your mind about computing. It’s gone from deterministic to probabilistic to linguistic. It’s not just for calculations anymore.
How is your organization preparing for Generative AI? What challenges are you facing? Drop a comment or reach out—I’d love to hear from you.