From Self-service to Self-sufficiency

Going by the sheer usage of the word, it would seem apparent that many think self-service represents the pinnacle of any application’s user-friendliness. But as we continuously investigate real-life situations, this approach is evidently inadequate to deal with diversity within workforce.

As we saw in our last blog, instant data-access on its own is a worthy objective, but it falls short of grappling with today’s ever-increasingly complex business landscape. What we truly require is data-linkage, so that we not just discover data but also can best-leverage data considering the context.

The way self-service is defined these days, it requires a certain level of technical / data proficiency to harness its potential. If the business-users are high-skilled data consumers, they can extract the best from the application and possibly bring their work to fruitful conclusion. However, in a diverse workforce environment, we have professionals that contribute to the business side of organizational function, but whose mandate extends to data-driven understanding and decision-making. This kind of professionals are liable to be diagnosed with data-deficiency if the system works only for a few.

Self-sufficiency, not just self-service

When we pondered over the data-linkage and embedded intelligence for our enterprise platform, we realized the necessity of wrapping the core function with a ‘conversational’ layer. This layer actually defines and links the interfaces throughout the enterprise system.

It puts a deceptively simple layer on the top of what really is a sophisticated interplay of disruptive technologies.

While self-service operates under the assumption that the user knows what needs to be done and how, it’s one-size-fits-all nonetheless. We thought that it’s undemocratic that the only a select team could benefit from the power of data, and that even these people are expending efforts which could best be utilized elsewhere.

Self-sufficiency, on the other hand, is conversational by design.

Here, the user is guided with intelligence throughout his journey so that the data-based insights can be transformed into insights-driven action. It feeds the business-user with proactive, contextual intelligence, so that the data is easily understandable and actionable. It provides proactive informational prompts where the probability of user getting stuck has been found to be high.

All the complex functionalities that lie underneath the enterprise platform will be rendered inefficient if the user interface is purely function-oriented. Therefore, a human-centered design is essential in simplifying the complex business processes and enabling the user to connect the dots.

With the ‘conversational’ design encoded in the DNA of enterprise applications, the utility and profitability of the data is greatly amplified. What takes a well-versed data consumer a lot of effort and time, is now easily achievable by any business-user, irrespective of his area of expertise.

This expertise-agnostic data-empowerment leads to an overall leap in workforce productivity and operational efficiency. As we move on to the next orbit of enterprise operations and collaboration, the human-centered ‘conversational’ design is as significant as the disruptive technologies at play.

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