How can large, complex enterprises behave like startups with non-linear moves, while maintaining resilience?
The Live Enterprise model helped Infosys increase its market valuation from $30 billion to $50 billion, adding $20 billion (66 percent) in that five-year period. Importantly, it provided enterprise resilience during the COVID-19 pandemic, moving 240,000 workers from office to remote work in a matter of days, and actually surpassing previous year financial results in the quarter ending June 2020, in the heart of the global lockdown. Infosys has also helped numerous companies make the transition to digital technologies and resilient, sustained performance.
The promise and peril of the digital future has been forecast for years, from turn of the century dotcom boom and bust, through the rise of mobile applications and social media, and more recently through Industry 4.0. What’s changed is that exponential technologies like cloud, mobile, AI, open source and internet of things have matured and converged.
Globalism has spurred the rise of the corporate city state, where large enterprises have additional societal responsibilities in addition to, or perhaps even because of their role as generators of financial returns. And of course, the COVID-19 pandemic was the match that lit the tinderbox and dramatically accelerated change. We see this manifested in seven areas or domains with traditional and Live Enterprise perspectives.
Table 1.1. Evolution of Operating Model Elements.
|Operating Model Element||Traditional (from)||Live Enterprise model (to)|
Command and control
Functional, line of business based large teams
Technology as enabler
Self-organizing work teams
Cross functional and platform-mindset based small teams
Anytime, anywhere workplace
Distributed agile processes
Technology as strategic differentiator
One size fits all
Distant from input
Offline, periodic analysis
Proximity to source
Instant micro feedback
Distributed organizational knowledge
Insights for review
Predictive and prescriptive
Connected and curated organizational knowledge
Insights to actions
Anytime, anywhere, any topic learning
Features and functionality mindset
Designed for known requirements
Designed for evolvability
Program-driven large change
Sigma of micro changes
Significant change level
Building new routines
The very nature of organizations has come under pressure. Hierarchical and even matrix models are simply too static in a world where, much like water follows lower-lying land, real authority and influence cut across traditional silos and evolve frequently based on customer and project needs. Organizations must be able to address many initiatives simultaneously and update structures quickly based on market needs.
Employees, especially digital natives, count on anytime, anywhere, personalized and predictive experience, whether work occurs in an office building or from home.
Value chains have changed. For decades value chains focused on process effectiveness and product and service delivery, fulfilling value propositions to customers and other beneficiaries. Supply chains delivered goods from source of supply to the end consumer in a high quality, timely manner. But now enterprises must consider responsive value chains that can be re-configured quickly for changing business needs, have zero latency, are circular in nature and are part of an ecosystem. Further, they must address labor practices, worker health and alternatives in case of sudden supply disruption.
Decisions are the triggers of the digital economy, the actions that initiate response and provide it shape and direction. Deterministic rules engines have accelerated decision-making, but more is needed. Like the human mind, which is wired to see patterns, the explosion of data requires new ways to process real-time information in conjunction with insights from past experiences, to create machine-based intuition and action.
Talent has progressed from a cost to be minimized to source of competitive advantage. The so-called “war for talent” is actually a talent famine, as broad swathes of in-demand skills are greatly underserved. This also applies to talent sources, which are no longer a small batch of traditional business schools but entire new talent pools and learning pathways to groom the workforce of tomorrow.
IT systems are evolving from static processing engines to agents of change. However, many of them are designed for specific features and functionality and therefore struggle to evolve as newer features, functions and experiments have to be rolled out.
Change management is changing as well. Gone are the days of rigid, top-down, novel-length communication plans and forms-driven change. When program operations are driven by daily scrum standup meetings, much smaller increments are needed to keep change initiatives in synch with the rapidly evolving world around it. The sigma of these micro-changes helps bring about larger change during a transformation. Change interventions are instituted bottom up in a micro-change—aided by changing routines in the current process (routine +1) and by providing the right cues/nudges and rewards/recognition, leading to the ultimate behavioral shift and the desired outcomes. As users are empowered to drive change, convenience, adoption, behavior and value realization replace system go-live as the metric for success.
Excerpt from The Live Enterprise: An Evolutionary Operating Model for the Future by Jeff Kavanaugh and Rafee Tarafdar, p.14-19 (McGraw Hill January 26th, 2021).