Amid the focus on how trends in automation, analytics, and artificial intelligence (AI) will reshape the workforce and supercharge productivity, the business opportunity for early (and bold) movers often gets relegated to the background.
It is easy to look at these as capabilities that all companies need to (eventually) develop – but the larger gains may lie in treating these as core competencies, in the strict sense that CK Prahalad and Gary Hamel first described the concept.
While purists may bristle at that assertion, it is not made lightly. By way of example, it is now abundantly clear that fully realizing the potential of AI is not simply a matter of developing esoteric algorithms in a data science “lab.” It requires a cultural shift and embedding a new mindset across the organization. Similarly, effective use of advanced analytics to get closer to the customer first and foremost requires common ground between business and IT.
The good news? Starting down this path is easier today than it has been in the past. The playing field is near level when it comes to knowing what potential competencies to chase down.
Consider how some venerable companies developed their edge. There were essentially two templates: one from hi-tech companies such as Apple, and the other from corporations such as Nordstrom.
Apple’s core competency lay in design, initially applied to the ultimate productivity tool – the personal computer. It wasn’t easy for competitors to even foresee the potential of industrial design in this space, much less actually go about developing it as a competency. Other tech companies also consistently surprised you with their choice of competencies, but few at the time were as outré as Apple’s.
On the other hand, Nordstrom had a relatively simple model – though mimicking its success was anything but. Nordstrom’s competencies centered on delivering a remarkable customer experience. As numerous business-school case studies can attest, the company was able to not only crack the code but also somehow build a competitive advantage that relied on both differentiation and low costs.
A more readily replicable template has emerged now, driven by breakthroughs at the intersection of analytics, AI and automation. More importantly, it allows you to directly impact the product/service experience (for the most basic example, think chatbots).
Take robotic process automation (RPA), a subset of automation that can be applied generally across all industries. You may or may not agree with the timelines in the press, you may be ethically torn about the implications, but you can’t deny it will be a game-changer for many of your manual processes. Embracing RPA early with the right governance will allow you to be at the vanguard of creating value – perhaps even get in front of addressing the key employee concerns.
This is even more true of advanced analytics and AI, increasingly used in concert to maximize value. Today’s reality is very distinct from the noise surrounding big data. Separate the signal and the message becomes clear: use of AI and other advanced analytics will distinguish the serious players from the casual gamers. What the hype around big data accomplished was to bring their potential into sharper focus.
It seems blindingly obvious – until you realize that many successful companies are still only tentatively treading water. What does that mean for you? It means a once-in-a-generation opportunity to be among the first in your industry to develop these as real competencies along with the surrounding ecosystem (such as training and KPIs). A core competency becomes hard to replicate largely because of the depth of experience early adopters are able to acquire – and industrialize.
For organizations willing to take the plunge into full-on adoption, the benefits will be outsized. Capability in these areas is just table stakes. Go bold.
Navjit Gill is a Strategy and Transformation expert and works at the confluence of business and technology for some of our biggest clients in North America. You can contact him at email@example.com.