AI for business

Change the player, change the game

Adding AI to everyday workflows will have a transformative effect on the channel, writes Niall Kitson
Image: Stockfresh

16 October 2018

A recent survey conducted by iReach for Verizon Connect showed, once again, that business leaders are sold on the idea of emerging technology but haven’t a clue how to apply it. Eighty-one per cent of respondents said embracing digital technology would benefit their businesses, with the top three areas of interest being technology transformation (52%), customer experience transformation (38%) and supply chain transformation (23%). Furthermore, almost two-thirds (65%) said making more of their data was a priority, but examining fleet data was considered interesting by a meagre 41%.

Commenting on the survey, Derek Ryan, vice-president, Verizon Connect, said it was “positive to see that almost seven in 10 Irish business leaders are looking towards data to drive future growth and competitiveness”. The report, however, notes a gap between ‘saying’ and ‘doing’ with 40% knowing they should be more active in exploiting their data.

Guiding the process of digital transformation, data science and new customer service platforms is the controlling hand of artificial intelligence. In-house data scientists are expensive but you can use AI to generate insights at a fraction of the cost. Depending on where you sit AI is either a positive disruptive influence or a threat to the existence of the channel. Vendors favour AI as a means to do more with fewer intermediaries, while the channel looks for ways to turn vision processing, natural language processing, and predictive analytics into productivity tools. You could say the competition is a case of ‘value v value add’.

The monster
The vendor/partner tension was summed by up Mark O’Halloran, head of commercial services with Coffin Mew, in an article for where AI was called “an existential threat to the channel”. In his piece, O’Halloran broke down the functions of the channel into the broad headings of logistics, warehousing, and sales, and how they face being taken back by the vendor. To take them in turn, the role of logistics should be an easy win for the channel. Not so. The ability to move inventory and process returns and recalls are simple functions on the face of it, but what if the times, places and dates of deliveries could be controlled remotely by the vendor? This could be something as simple as when to deploy vehicles based on time of day, volume of recall or weather conditions that could impact overheads.

Point two, warehousing, poses the following challenge: under today’s model the vendor produces inventory which the partner takes responsibility for storing, having secured favourable terms from a warehouse owner. Maybe no longer. Through AI a vendor can identify a network of warehouses, find spare storage capacity and rent it direct, meaning instead of filling up one location you could use multiple locations Airbnb-style.

Point three, sales. The channel prides itself on relationships with retailers and buyers, the ability to secure favourable terms, look after pricing and presentation. If controlled centrally by the vendor, pricing can be based on inventory levels based data fed direct from the retailer. Orders are fulfilled and despatched with minimal human contact bar the aforementioned lorry-loading.

Keeping both sides together are the SaaS providers promoting AI as a mutually beneficial technology, marrying greater efficiency with the ability to devote more time to soft skills like fostering client relationships. Salesforce has invested heavily in such a customer-centric vision of the ‘Fourth Industrial Revolution’ through its Einstein platform.

Vice president of solution engineering Carl Dempsey draws attention to an internal report that found sales staff devoted only 32% of their time actually selling, with handling e-mail and inputting notes into a CRM being significant time sucks. He says that through tools like Sales Cloud Einstein “you can let AI automate activity logging, identify high-priority e-mails, and create new contacts… This allows you pass off that admin work and start spending your time in more productive ways that ultimately makes you far more relevant to the sales channel.”

Dempsey says that while there are some simple indicators of which clients are most likely to close a deal – company size, signing up for a free trial or downloading a white paper – Einstein has also managed to gain insight from unexpected sources. “One company we work with found that the version of mobile operating system the person was using when they registered as a lead was strongly correlated to how likely they were to convert. This piece of information was captured by default by the form but Einstein identified this pattern as a data set… and it drove the company’s lead qualification process in a new direction.”

Another company synonymous with AI is IBM which has used its Watson platform to play matchmaker within its own sales department to put together teams with complimentary skill sets. Dr Elizabeth Daly of IBM Research Ireland explained in a company blog that “forming the right sales team for a new opportunity is vital and depends on understanding the roles required for the opportunity and then finding the right people to fill those roles such as managing the relationship with the client, having a deep knowledge of the product or being able provide an overall technical architecture seeing how all the products can fit and work together.”

Daly’s work on the Opportunity Team Builder for Sales Teams looks at performance using three models: role recommender, team recommender and win prediction model. The scale may be beyond most channel partners but the idea of mobilising teams assembled using a statistical model of success should be manna for sales managers.

Another area of progress is in chatbots, which Dempsey says are capable of handling as much of a third of simple customer service queries. He notes that “with help from the bot on heavy volume simple tasks, their agents now have more time to work on complex customer issues or value-add activities”.

It’s worth noting that IBM and Salesforce have collaborated on Watson Discovery, a customer service platform that delivers advanced solutions to junior representatives.

For the moment Dempsey says expectations need to be managed. Despite Einstein processing 1 billion predictions per day additional use cases will evolve as sales teams become more familiar with the technology.

The Revolution, and the debate, goes on.

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