All business leaders have dreamed of changing the course of their enterprise: breaking the cycle of primitive landscape renewals, temporary fixes, budget constraints, and traditional acceptance of “more of the same”. Sadly, despite the recognised need for change, those dreams rarely ever come to fruition.
The truth is, though, that change is possible – especially today. Automation and artificial intelligence are at businesses’ disposal, and capable of rapidly transforming how they operate without the enormous manual efforts typically associated with it.
In addition, approaches like that of design thinking give enterprises the power to transcend the past and uncover opportunities even before they unfold in order to create new and unprecedented value.
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But this holistic transformation requires thought and planning; is greatly accelerated by an experienced guiding hand; and is possible only when an organisation can express the core of its business through a simple cohesive model.
This transformation isn’t another call for enterprise unification. Diversity is absolutely necessary, but islands of diverse data sets, non-interoperable systems, isolated processes and people create complexity, which makes core transformation a nightmarish effort. What organisations see is a fog of information so dense that it blocks out knowledge, insights and meaning.
Organisations have, no doubt, attempted to penetrate this fog with integration efforts. And these attempts have likely been manual, which costs a lot of undue hardship and, of course, money.
Thankfully, manual integration is no longer the only option. Companies can now integrate people and software – a model where one amplifies the other. For example, companies can create a layer to automate the curation of knowledge from across enterprise silos – its systems, processes and people.
It can do this while ‘firelaning’ each silo’s inherent and unique complexity, allowing enterprises to retain its inherent diversity. This combination allows an enterprise to form the basis of a simple, coherent model that can achieve a number of different outcomes. These outcomes can range from efficiency optimisation to agility for innovation.
This model can also help enterprises to embrace artificial intelligence, since it makes enterprise knowledge machine-readable. This helps to simplify work, giving room to innovate and bring creativity and inventions into everyday use without having to bring in outside resources.
That’s the power of artificial intelligence: it creates the foundation for an environment where mechanisable, repeatable activities can be modeled and precisely formulated to be automated, while people free themselves up to pursue new ideas. It also brings change to the important things without the crippling costs, and without turning off the engine and bringing people to a grinding halt.
For example, a technology company was looking to create a superior cross channel sales and self-service experience for its B2B customers. Its transaction processing landscape relied on manual intervention, but it knew that the first step to reformation was to pursue aggressive digitisation. However, its transaction-based customer service model and lack of customer-level 360-degree reporting limited its view of customer relationships and request continuity.
In short: it was awash in data, but had little insight into how it could transform its transaction processes into something more relevant for its customers.
Years of design thinking in the enterprise arena has shown the immeasurable value of an organisation’s ability to proactively find the most pressing customer pain points. Simultaneously, it also enabled the technology company to automate the curation of pre-existing knowledge locked within their systems, customer-service staff and more.
Based on this knowledge, and the findings from the design thinking endeavour, it then helped to simplify transaction processes — even as they focused on supporting new customer experiences.
This transformation yielded significant results. Process automation reduced operational expenses by 30%. For customers, it helped cut nearly 2 million hours in wait time by improving the accuracy of responses and accelerating time-to-resolution.
Customer relationship management processes were also enhanced considerably. For instance, the intelligent routing capability that digitisation brought in automatically assigns customers’ requests to agents who are most familiar with the problem at hand. These customer-centric features helped to streamline both the service experience and improve overall customer satisfaction.
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This company’s success can also be attributed to the use of intelligent platforms. At a conceptual level, platforms give enterprises the flexibility to assemble capabilities as and when they need them. And specifically in the context of knowledge-based revitalisation, they help create both the foundation and an enabling environment for renewal.
But to make any enterprise transformation timeless, there must be significant improvements to known problems, and also the simultaneous finding of unknown paths to bring simpler, richer, more experiential and relevant alternatives to customers.
This takes cultural transformation and introspection. Enterprises will need to take a step back to explore fundamental questions about what they’re doing and chart a clear vision of where they’re going before embarking on this kind of renewal.
Sourced from Sanjay Purohit, chairman of the board and managing partner, Infosys Consulting
