Step inside the e-commerce department store of the future and take a look around—a lot of things are still the same.
There’s the front-line telephone support team fielding customer calls; there’s the web team reveling in well-planned systems maintenance schedules; there’s the maverick developer reimagining how internal platforms should be run and engineered; and there’s the enthusiastic, interpersonal team leader whose job it is to rally the troops and create department unity.
The difference is, in our near software-based, data-driven future, a lot of these roles are all the same person. Why? Because it’s a bot.
The Quest for a Mature Digital Culture
The power of software to create these diverse behavioral types and personalities can go beyond any level of interpersonal human training. We can use software robots (or “bots”) to perform repetitive, measurable, and quantifiable tasks.
But this is not the end of the line for humans. If we diligently and conscientiously engineer our progression to bot-based support staff, we will be able to move people to higher-worth, value-adding tasks that require advanced human ingenuity, unbridled creativity, and deeper levels of empathy.
This isn’t a possible future scenario or distant call to action. This year’s imperative, to live a more socially distanced existence, has propelled the use of online shopping. Consumer goods companies and professional services organizations have had to take huge leaps forward to be able to trade in a predominantly online format. The idea of cloud-based, web-driven business has transformed digital development plans from aspirational to foundational. According to the Dell Technologies 2020 Digital Transformation Index (DT Index), 78 percent of retail and consumer goods companies have accelerated their digital transformation programs this year.
But of course, some businesses in this sector have done more than others. Just 44 percent of firms say they are reinventing how they deliver digital experiences to customers and employees. Only 40 percent could say they were able to transform because they had the right technology to work at the “speed of business”; just 33 percent were aided by a “mature digital culture.”
In the recent past, these figures wouldn’t be problematic. A slight lag or gap here and there could have been compensated for or narrowed further down the line. But with the world now changing at speed, we no longer have that luxury.
However, software bots are the “employees” that can help in this digital culture. Usually referred to as part of robotic process automation (RPA), bots are not just chatbots for text-based conversations (although they can perform that function, too), they are worker bots ready to take on tasks that sit inside defined human workflows to make business operations run more smoothly.
A Groundhog Day-Cycle of Repeating Black Fridays
If we are facing an onslaught of trade that represents a Groundhog Day cycle of repeating Black Fridays, we are accumulating a powder keg of tension. Businesses can release the pressure valve here by automating workflow components with a battalion of bots and other artificial intelligence (AI) tools to deliver fault-free, real-time service.
But again, according to the DT Index, just 29 percent of retail and consumer companies are transforming their services and consumption models with AI in response to recent upheavals. This suggests that many aren’t primed to call in a new team of intelligent support workers from the cloud. In fact, many retail and consumer goods companies have even downgraded their one-to-three-year investment plans for AI, from 30 percent in 2018 to 26 percent in 2020. Their one-to-three-year investment plans for cybersecurity have similarly dropped from 52 percent in 2018 to 40 percent in 2020. Although 25 percent are now planning to invest in robotics, up from 9 percent in 2018.
How to Build Up Your Bot Workforce
Building up a bot workforce begins with using supporting software structures. For instance, individuals’ workplace roles can be deconstructed using “task mining” techniques, during which user interactions with apps and data are logged and tracked. These insights can then be used to define wider process mining structures that combine individuals’ tasks into team and company actions to pinpoint where bots can be deployed. Dell Technologies has been developing RPA systems to operate a large estate of “digital workers.”
Businesses also need to think about how they can scale their bot workforce, and be ready to go big. To start with, we built a single bot that would run once a month—for a single 24-hour period—to process multiple documents related to renewal quotes for equipment across departments. This one bot took on a job that consumed 500 people every day. The success of this one bot clarified and validated use cases for bots more widely and demonstrated that bots can absolutely allow their human counterparts to be more productive and effective in their higher-value roles. It essentially proved that there’s more to bots than just hype.
Selling the Sizzle While the Bots Are Hard at Work
AI can make bots intelligent. In combination, AI + bots can optimize a full spectrum of operations, including pricing, so organizations know how their products are priced versus their competitors, what would be the appropriate price for a product, when to launch special seasonal offers, and how to set up rules to change prices on-site dynamically. In working practice, an AI-driven price initiative provides insights and recommendations to set prices based on various strategies, which frees up human time to do more creative work that drives growth and productivity.
Product relevancy engines are another example of AI + bots in action. These AI-powered bots effectively scan thousands of products from the product catalog and show more relevant products to customers based on their intent. These bots can manage a large set of rules or strategies in real-time as customers interact with the site and find out what customers want to buy or when customers are open to slightly different purchases to maximize sales opportunities. This bot intelligence is driven by a lower or a higher level of algorithmic logic based on affinity with the customer’s behavior and preferences, which allows the bot to prioritize recommendations and ultimately push forward to fulfillment.
For bots to form part of an intelligent, end-to-end business plan, they need to able to work at the backend server level, the middle tier application processing level, and the frontend user level. An end-to-end bot team sees an organization carefully engineer the union between bots and people so that one group feeds vibrantly and productively off of the other.
Further still, an end-to-end business using bots knows where to carefully draw the line. Although bots are pre-programmed with sufficient knowledge, the smartest ones will learn more work functions as they develop. Some graduate and get smarter, some stay static, and some (just like people) are ultimately retired if their function becomes redundant or obsolete. As we can see from the Institute for the Future’s seminal report forecasting the next era of human-machine partnerships, in collaboration with Dell Technologies, both humans and bots will still need training, support, and maintenance. When a bot or any other element of an AI platform can’t work out what a human being is asking, what a business task requires, or what to do next, it performs a “human hand-off” and offloads the task back to a real person.
The good news is that for every human hand-off problem resolved, the bots get smarter and Black Friday becomes less frantic and more profitable.