It's rapidly become a familiar question - what happens after the pandemic in terms of what the ‘new normal' of work will look like?
The combined efforts of AI and search-based analytics specialist, ThoughtSpot, and Harvard Business Review Analytic Services resulted in a study that provided some options, which were followed up in an online meeting with ThoughtSpot CEO Sudheesh Nair.
The objective of the survey was to establish whether businesses thought it would be beneficial to give customer-facing workers richer tools with which to interact with those customers directly, without having to default to ‘I'll get back to you on that question'.
With COVID-19 obliging more and more customers to locate, source and purchase products and services online, the underlying question was whether businesses felt it would be advantageous if their first points of contact with customers could answer more questions, up to the point where they effectively `make the sale', even if they don't do the paperwork. That way, runs the theory, may lie real customer satisfaction.
There would, of course, be little point to this story if the majority of businesses felt there was no advantage in such capabilities. So there should be no surprise that HBR found that, indeed, the interest is instead high.
The report - The New Decision Makers: Equipping Frontline Workers For Success - polled 464 business executives across 16 industry sectors in North America, Europe and Asia Pacific. Respondents agreed the thesis that they would be more successful when frontline workers are empowered to make important decisions at any point they are needed. The one small problem with this was that right now only a minority had made any significant move to equip their frontline workers with the resources to do so in practice.
Empower the frontline…but how?
Thoughtspot CEO Nair believes that the most immediate issues post pandemic will revolve around commercial real estate and workplace design and functionality if the majority of those who have been obliged to work from home decide they would like to continue with that regime. Of course, it's equally possible that employers may want to encourage this attitude, for worker satisfaction as well as possible savings to be made in OpEx and general overheads.
If ongoing home working becomes a key element of the new normal, that will change many things for businesses, but all of them will hinge around analytics and the widest access to data that is possible. For example, Nair notes that, before ‘coalface' workers can be empowered, businesses need to have knowledge about the best available talent the business can attract, given that geography is no longer an issue:
I personally have struggled to get hiring managers to go out and hire where the talent is. We have offices in Bangalore and Sunnyvale, so let's just hire around there because centre of gravity is important - that's been the conventional wisdom. The problem is there could be an amazing designer in Costa Rica. There could be great AI talent out of Ukraine, or in Bulgaria. Whether you're in Sunnyvale in California, you might as well be in Bulgaria, time zones notwithstanding. The place where analytics will play is when you have remote culture, people are distributed everywhere.
Identifying such talent will be a problem without the right tools, even though much of what a business needs to know about such talent is available as data. What's needed are analytic tools that can search for that kind of data, such as things they have written that can give clues to the way they think and code they have produced which indicates their inherent code quality and levels of productivity.
Nair sees this leading to a new model of recruiting, retention and encouragement of distributed workforces, and that will depend on the quality of data they assemble.
Be autonomous, not an automaton
One of the factors that is likely to be an important by-product of the move to more permanent remote working is the likelihood that staff will not only be expected to act more autonomously than when tethered closely to the office mothership, but will also require new tools to help them work closely with the customers they are in contact with.
What is more, the old demarcations between those allowed to directly communicate with customers and those not allowed will need to fade away quite quickly. The communication delays inherent in the sales team asking variations on a customer query of the design office, production department, accounts etc, before getting back to the customer with a mashed-up answer have to go.
There are already suggestions that the imposition of remote working has created a situation where businesses are realising staff can be trusted to work, not take downtime. Indeed, it seems there are signs that many are happier, less-hassled (especially losing the rigors of commuting) and more productive. They are, it seems, responding positively to the greater responsibilities - both personal and professional - and are of a mind to take on more.
So, imagine that, if the right information is available, a ‘techie' might well be able to not only talk through the technical solution to a customer problem, but also related business issues involved in turning design into reality.
All of this, of course, hinges on the availability of that right information, and increasingly that means analytics tools available to them on their remote desktop. This is where Nair sees a growing opportunity for ThoughtSpot in this need to now empower the ‘coalface' workers:
Is it a way to sell more stuff, or is there something more existential? If you unpack it, you learn that consumer aspirations about how a business should interact with them and how the business should serve them, has changed because of a couple of cool things.
The first of these is the increasing use of automated Robotic Process Automation and machine learning. The other is the rise of analytics and AI. Analytics can identify and pull together all the data relevant to that customer and use that data to derive answers that will help the customer reach a decision, while AI can extend that by using what the system has learned to extrapolate out to the as-yet-unthought, unconsidered possibilities and, yes, pitfalls. This gives the employee significantly more scope and responsibility, but it can easily bump up against internal communications problem. As Nair observes:
The challenge there is you cannot teach all the business people SQL and coding, and you cannot teach the business analyst all the nuances of business.
There is still that need for tools - or a tool - that can both bridge that communications gap and provide the AI and analytics in a form that does not require to be learned from the ground up. That is one of the claims that Nair makes for ThoughtSpot, given that its user interface is, at heart, a search engine. The difference is that it uses machine learning to build its own knowledge of what the user typically searches for and AI to perform functions, such as extrapolate on from that knowledge, to identify new lines of search and enquiry that can be added to the process of analysis.
And it can search whatever data is available, not just the databases of a single business. To this end, ThoughtSpot has a growing range of partners amongst the third party public data providers such as Neilsen, which has one of the largest repositories of consume sentiment data available. Nair says:
The complexity of the data, complexity of the relationships, and complexity of the queries are making it harder to deliver simple but relevant insight to the business. So all we are trying to do is democratise that.
`Democratise' is an apt way to look at this issue. The ThoughtSpot goal of creating an analytical tool that has the ubiquitous search engine UI as its start point makes building insights of value an extension to so many non-analysts' existing experience. A good part of the `black art' of analytics is set aside.
In the same way, the realisation that the necessity of remote working is probably proving an valuable by-product of the pandemic means that the democratisation of the use of data spreads the possibility of staff adding new value to the business as whole.