The Accelerating Downfall of Fortune 500 Companies: A Wake-Up Call
We’ve heard time and again about organizations getting removed from the list of Fortune 500 and the speed of this eviction seems to be ever-increasing.
The key reason (nothing new here) is that these organizations have failed to innovate as they were not able to overcome the inertia resulting from their existing processes, technological trajectories and needs of existing core customers.
However, the reason to ask is why were they not able to overcome this inertia? Could their organization structure and resulting operating model be at play behind this – the root cause diagnosis for this seemingly consistent disease.
The Challenge of Scaling AI
Also many companies have been testing, prototyping and building AI solutions, yet only a significant minority have been able to successfully scale and extract returns from it.
Companies have been sold on MLOPs, but that is solving a different set of customer needs – how to manage, roll out, deploy and maintain AI models in an industrialized manner.
The Importance of Human Processes in Innovation
However, innovation management is a much bigger concept that has interplay between humans, technology platforms and processes. For innovation to be made systematic (and scalable) within organizations, we would need to address the human factor, organizational structures, and resulting operating models.
Tailoring Your Approach: Why One Size Doesn't Fit All
The AI (or innovation) organizational structure or operating model is not a one-size-fits-all approach.
An experienced craftsman will need to analyze the organization’s existing situation with respect to investor & market needs, industry dynamics, resource availability or scarcity, organizational culture, etc. to understand the explorative vs. exploitative nature of innovation needs to create the most appropriate model for an organization.
What might work for Google may not work for you – Google puts a lot of emphasis on the entrepreneurial nature of the people they hire.
This is a small teaser why an organization should carefully consider and plan the human related processes behind innovation.
Data Design could be your partner in discovery and definition of this key process – a process that could be the key to your survival and growth.
Your Partner for Success!
Lessons Learned
- Understanding Inertia in Big Organizations: The largest corporations often struggle to innovate due to the inertia of their existing processes, technological trajectories, and customer needs. The lesson here is the critical need to constantly reassess and adapt these elements to stay competitive.
- Innovation Management is More Than Technology: Innovation is not only about utilizing new technologies like AI; it also involves the interplay between humans, technology, and processes. The lesson is the importance of human-led innovation management and the integration of technology with human processes.
- Scaling AI is a Challenge: Despite the promise of AI, only a small percentage of companies have successfully implemented and scaled AI solutions. This teaches us that innovation isn't just about adopting new technologies but also about effectively scaling and integrating them into business processes.
- Tailored Approaches to Innovation: There's no one-size-fits-all approach to innovation or AI-related organizational structures. What works for one organization might not work for another, emphasizing the need for customized innovation strategies based on an organization's unique circumstances and needs.
- The Importance of the Human Factor: Organizations should not underestimate the role of the human factor in innovation. The lesson here is that human-led processes often determine whether a company merely survives or thrives.
