That may be the biggest question among commercial leadership teams right now as they validate learnings from the last two years and debate new models for the new normal.
That validation is critical. The organizations that are leveraging the provisional insights hard-earned in times of rapid change, through multiple fielded experiments, have the distinct advantage of evolving from experience.
Talk of future commercialization models once imagined a shift to hyper-efficient digital channels with automated relationship engines. What the industry has learned is that a simple transfer of resources from high cost / low frequency interactions and low cost / high frequency channels is not enough.
Instead, the new optimization loop requires both a highly effective field and highly efficient digital. In the new models we know the customer as well as the technology; know the data as well as the business. Increasingly the industry is putting relationships first, then fueling those relationships with digital amplification and improving them with transparency to data and signals of intent. The end game is nothing less than data-driven value creation. Even as human interactions remain front and center, our machine-learning systems will start acing tasks that eluded them until now. That is, helping managers navigate oceans of data—sometimes messy, or siloed, or locked in brittle dashboards—so we can aggregate what matters and draw insights from data to inform decision making.
