“Never Let a Good Crisis Go to Waste.”
~ Winston Churchill
Next to the fact that many people in the world find themselves dealing with personal loss, we are also entering a period of great economic uncertainty and volatility. It is likely that the economic impact of COVID-19 will exceed anything we have experienced since the end of WWII. Simultaneously, we are at an inflection point of unprecedented technological growth. Artificial intelligence has been anticipated to add 16% ($13 trillion) to current global economic output by 2030, representing a techno-social shift that will transform the economy more than any of the previous three industrial revolutions.
Market downturns typically drive sustained wedges in competitive performance. But the mass introduction of artificial intelligence in the midst of a global recession will usher in an era of business in which winner-take-all models increasingly dominate. The combination of these two megatrends is set to turn the existing digital divide between the digital “haves” and digital “have-nots” into an insurmountable chasm.
McKinsey’s Kevin Laczkowski dubbed the top 20% of companies that emerged from the 2008 recession ‘resilients’. These are companies that did not have any specific pre-crisis advantages (e.g. existing portfolio, technology, IP, etc.). Instead, they managed to achieve small leads, which they then exploited over the following 10 years. Compared to non-resilients, the success of resilients was primarily determined by speed and discipline; they moved 12-24 months earlier, reduced operating costs by 3x and increased revenues by 30%.
In the current crisis, belt tightening alone will not provide the organizational fitness required to become a resilient. In the era of AI, success demands that we leapfrog obsolete practices and combine people, processes, data and technology in ways that we never have before. Those who seek shelter to wait out the storm will find catch-up elusive, even when economic conditions improve. Whereas those who seize the opportunity to reinvent organizational fitness will define the new normal.
Simplicity – Shedding Layers of Bureaucracy
It is precisely in a time of crisis that inefficient and extraneous processes start to become more apparent. There can also be more latitude to challenge the norm of how inadequately business may have been allowed to evolve. Thanks to the longest bull market in history, many companies have enjoyed extraordinary growth over the last ten years. Even companies that have tolerated poor organizational fitness benefitted from the rising tide. It is only because the economy was growing so fast that it was possible to disregard limiting processes. Sustained rapid growth has meant that companies have created more layers of bureaucracy and overhead. Every time a new employee was hired, a new product was developed, or a new market was entered, a new layer of complexity was added on top.
The challenge during a downturn is that near-term cost pressures yield efforts to “lean things out” function by function, with each executive or manager told to “make cuts to what’s under your control.” But belt-tightening exercises alone only solidify existing inefficient and siloed processes. As Peter Drucker expressed it, “there is nothing quite so useless as doing with great efficiency something that should not be done at all.” The fact is that it is easy to add stuff, but hard to intelligently remove what no longer contributes to the core of a company’s value generating engine. Many leading companies have tolerated obsolete processes, because they were cash rich in the immediate-term and have not yet taken longer-term strategic imperatives to heart. The crisis we are now in is an invaluable opportunity to relentlessly do more with less by shedding burdensome layers of processes and bureaucracy.
There are many parallels between the Third and Fourth Industrial Revolutions. In the late 1990s the rise of the internet fueled a period of massive growth. Companies that attempted to layer an internet presence on top of existing business models eventually failed. Simply adding a website to brick-and-motor retailers was not the recipe for Amazon, adding a website to Blockbuster was not the recipe for Netflix, and adding a website to a taxi company would never have giving rise to Uber. After the dust of the dotcom era settled, the companies that prevailed were those that used Internet technology to create wholly new business engines.
Like the introduction of the Internet, the introduction of AI into mission critical business processes comes with a similar mandate to think differently about value creation. In 2011, Marc Andreessen proclaimed, “software is eating the world.” But by 2020, it is safe to say that software already ate the world and now AI is eating software. The reality of artificial intelligence brings with it an entirely new world full of opportunities and risks. And while leading technology companies like Google, Amazon, Facebook and Apple (GAFA) have already created tremendous value with AI, the greatest value that will be generated by AI in the next 10 years will come from more traditional sectors.
More than intelligent automation, AI enables oversight of massive streams of real-time data. Incremental applications can speed time to market, reduce operating costs and increase revenues, but fascinating competitive transformations begin where AI breaks down conventional silos. AI’s promise is to allow business leaders a deep understanding of interdependencies across functional units and thereby facilitate more connected and coordinated systems both inside and outside an organization.
A full-scale reorganization is tough to pull off anytime, and particularly so in the throes of a major downturn. A winning strategy balances practical financial restraints against the potential for value creation. Initial steps do not necessarily need to cost a lot of money as long as each phase ends with a clear cut-off point and a go/no-go decision for the next phase. In this way companies can not only rapidly scale transformation, but also limit losses if one phase turns out to be less advantageous than originally envisioned. Success requires a roadmap that breaks transformation into overseeable and actionable steps with quantifiable ROI. Start with smaller standalone use cases that have surgical (precise) applications. That makes it much easier to build momentum on cases that provide a strong fit between desired business outcomes and technical feasibility. The roadmap needs to define how these smaller building blocks will be scaled and combined into a defensible moat.
Where to Start
Successful implementation of AI demands laserlike focus on a company’s unique value drivers. But these drivers may not be readily apparent. It can be incredibly alluring to invest time optimizing and automating processes that served past success, rather than future potential. That is why it is critical to start with a clean-slate-engineering approach. Consider, what is the actual job-to-be-done, and if you had unlimited options, how would your company deliver extraordinary value? Start from scratch using design thinking – before you start thinking in limitations (all the reasons why a new approach would never work), train yourself to think in limitless ways. In the best of all possible worlds, how would you provide for the job-to-be-done in a way that has never been done before? Use first principle thinking and root cause analysis to peel back layers of assumption. All too often we accept the established framing of a challenge, or chase after extraneous symptoms without considering the root causes and drivers of the solutions we stand to provide.
In light of macroeconomic swings, consider how re-clustering of activities would help. Re-clustering can take the form of a “clean sheet” approach, or a more incremental approach. Start by looking across all business activities to better understand where the job-to-be-done is being served and where it is not. Because AI driven transformation impacts many dimensions of an organization, experts from multiple disciplines are needed to ensure scalable, safe and valuable solutions. Cross-functional project teams need to include domain experts and specialists from AI, design thinking and change management. These are world-class challenges so working with world-class talent to apply best practices from across sectors makes good sense.
Ask yourself, in terms of resilience in the face of the current crisis, what critical system operations are vital to your organization’s mission and survival? How can you help instill the right level of urgency and charge your teams with finding opportunities wherever and however they can? Even in this severe downturn, there are pockets of growth. Where are they? Are they in select customer segments, direct-to-consumer retail, specific geographic areas? Realize that supply-chain resilience and customer loyalty are now at a premium. How can you apply AI in ways that make your supply chains more agile and provide frictionless customer experiences in response to real-time changes and at lower cost?
Defining the New Normal
Succeeding in the current business environment will require an appetite for big moves.
So, by all means, take time to ask critical long-term questions. Some companies will undoubtedly emerge leaner, stronger and more innovative. Have courage, if it were easy everyone would be doing it. Remember, you are embarking on an iterative journey; the point is not to get it right the first time, but rather to advance rapidly by learning from mistakes.
Rather than passively hunkering down, the global crisis demands that we relentlessly adapt and rebound as vigorously as possible. We all have an obligation to find ways in which each of us can make a difference by doing what each of us does best. It is not about resetting to the new normal, it is about actively defining what the new normal will be. A global recession is unavoidable, but the decisions we make now will determine how we emerge from it. None of us can say how long the current crisis will last, but as sure as sunrise, it will pass. Now is a time for decisive action, because when the sun comes up, you’d better be moving.