In 1990, Michael Hammer, an MIT professor, shook the business world with his article “Reengineering Work: Don’t Automate, Obliterate,” published in the Harvard Business Review. He argued that companies should not just automate inefficient processes but should eliminate them altogether. The focus should be on creating real value for customers, rather than making flawed processes better.
Hammer believed technology should be used wisely to enhance value creation. His ideas gained attention, especially with his book Reengineering the Corporation: A Manifesto for Business Revolution, which was recognized as a major influence in management literature. By the early ’90s, many Fortune 500 companies had adopted his principles, pushing the movement of Business Process Reengineering (BPR) forward.
So, what does BPR have to do with today’s AI landscape? A great deal. Hammer’s BPR framework rested on three key ideas:
- Rethinking and redesigning business processes to improve cost, quality, service, and speed.
- Creating new work strategies and managing complex changes.
- Using disruptive technologies to rethink traditional work methods.
Fast forward to today, and these pillars are relevant in the context of AI technologies. Generative AI and large language models can help businesses offer customer value in innovative ways. McKinsey reports that by 2030, generative AI could automate up to 70% of business processes, adding immense value to the global economy.
However, just like with BPR, the key isn’t to rush into automation. It’s about thoughtfully reassessing how businesses create and deliver value using technology.
Here are some important questions for organizations considering AI:
- What is your AI strategy?
- Where should you start?
- What will your investment look like?
These questions may seem basic, but they lead to deeper considerations. For example, your AI strategy should align with your organization’s mission. Starting points for AI adoption should identify both quick wins and long-term opportunities. And investment isn’t just about money—it also involves skills, culture, and infrastructure for long-term success.
Applying Hammer’s principles to today’s AI journey can guide organizations in navigating these complexities:
- Reimagine your organization’s purpose and processes.
For effective AI adoption, companies need to think beyond minor tweaks. They should envision themselves as AI-driven organizations, understanding their core mission and how they provide customer value. This might mean shifting from selling products to offering solutions, which could require changes to supply chains and customer relations.
Begin with manageable, impactful use cases. Focus on areas where AI can deliver quick benefits, such as automating repetitive tasks or improving customer service. Rather than trying to do everything, choose strategies that allow for learning and growth over time.
- Foster AI skills across the organization.
Adopting AI isn’t just a tech issue; it’s also a cultural challenge. All employees need to feel confident using these new tools. Companies should invest in training and create a culture that embraces AI instead of fearing it. This mindset shift will empower employees to focus on higher-value tasks. As Marcel Proust said, true discovery comes from seeing things in a new light.
Today, Hammer’s advice to “obliterate, not automate” resonates more than ever. AI has the potential to transform industries, but it requires clear leadership and a willingness to challenge the norm.
For those who missed the BPR movement, this is a second chance. The possibilities that AI brings for growth and efficiency are immense, but so are the challenges. Leaders should revisit Hammer’s insights and adapt them for this new AI-driven era. The time to rethink and reinvent is now. Let’s not wait another 30 years.
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