Top five AI and analytics trends for the future of work
In a number of discussions that I’ve had over the last few months with company leaders, it’s clear that the global business world is fast evolving into something nobody could have anticipated before COVID-19. This article looks at the importance of building intelligence-based capabilities to help us prepare for, sense and respond to disruption. In the same way that we had to reconstruct our financial and risk models after the 2008 economic crisis, organisations today will have to reassess their use of AI and analytics to ensure our businesses are resilient enough to withstand further shock from future black swan events.
Better data and models
Our ability to collect, organise, analyse and react to data will be the new differentiator in business. The radical changes in professional, personal and societal routines have resulted in unprecedented shifts in consumer behaviour. As a result, the historical data that fed many of our analytical models has quickly become out of date, incomplete and unsound. Organisations will look to conduct data and model audits to identify errors and weaknesses in operational, financial and risk areas. Underpinning this will be a new emphasis on data governance. We must take a forensic approach to real-time data capture across all forms and formats, both internally and externally. I also expect to see a new cloud-first business model become the standard. Cloud computing allows for data to be verified and stored securely, while still being available across multiple zones for deep analysis and insights.
Analytics led operations
Before COVID-19, there was a frequent disconnect between an organisation’s analytics and its strategic priorities. Now, even non-digitally native companies must put analytics at the very core of their operations. Accurate and timely data will form the backbone of all business units, from sales and performance forecasts, to procurement and supply chain optimisation. To achieve this, organisations will have to develop an analytics-led culture. This means not only including analytics leaders in all strategic discussions, but also embedding data-driven decision making from the ground up. I’ve seen first-hand how COVID-19 has created flatter, more agile organisations with empowered frontline employees. These employees should be given the analytical tools they need to make autonomous and informed decisions.
Businesses able to seize the opportunities created by digital twins can improve their predictive powers while reducing cost of service. As we emerge from the pandemic, more organisations will therefore turn to digital twins of their supply chains to better prepare for unexpected shocks and to build an intelligent and resilient ecosystem. However, with the increase of real-time data from rapid digitisation, I expect to see digital twins used not just in supply chains and manufacturing, but throughout all modern businesses. Using these models, we can experiment with a number of key variables, testing different scenarios and contingencies to proactively mitigate risks and extend capabilities across R&D, engineering, product management, and even sales and marketing.
Consumer focused automation
The surge in consumer call volumes arising from COVID-19 highlights the limitations of focusing only on human interaction in customer support systems. Post-pandemic, we will inevitably see a rise in automation in this area, with tools like voice biometrics and natural language speech recognition freeing up agent time and improving customers’ ability to self-serve. Analytics will also play a key role in enhancing the customer experience. By collecting data from a wide range of touchpoints, companies can gain a 360-degree view of their engagement levels. In my opinion, this is where AI is transformational, helping to pinpoint customers who are likely to leave or those who need additional support, and finding the best offers to retain or assist them.
When faced with black swan events, even the most well-honed and calibrated models quickly lose their predictive power. For example, financial models that use time-series, oil-price, or unemployment data will need to be rebuilt entirely. Several organisations are looking to increase the quantity and diversity of data available by using machine learning techniques to generate ‘synthetic’ data for model development. These vast sets of realistic data can be used to calculate risk measures, train predictive systems and stress test portfolios. Much of this work is still at the research stage, but I expect to see a growing interest in this area as we grapple with the impact of unprecedented events like COVID-19.
It is evident that this crisis has forced business leaders to reassess their analytics capabilities and accelerate their . In the world ahead, I see business leaders, including myself, embedding data driven decision making into all levels of our organisations to gain greater intelligence and resilience.
Automation of repetitive tasks leads to higher value work
Two-thirds of global office workers feel they are constantly doing the same tasks over and over again. That’s according to a new study (2021 Office Worker Survey) from automation software company UiPath.
Whether emailing, inputting data, or scheduling calls and meetings, the majority of those surveyed said they waste on average four and a half hours a week on time-consuming tasks that they think could be automated.
Not only is the undertaking of such repetitious and mundane tasks a waste of time for employees, and therefore for businesses, but it can also have a negative impact on employees’ motivation and productivity. And the research backs this up with more than half (58%) of those surveyed saying that undertaking such repetitive tasks doesn’t allow them to be as creative as they’d like to be.
“When repetitive, unrewarding tasks are handled by people, it takes time and this can cause delays and reduce both employee and customer satisfaction,” Gavin Mee, Managing Director of UiPath Northern Europe tells Business Chief. “Repetitive tasks can also be tedious, which often leads to stress and an increased likelihood to leave a job.”
And these tasks exist at all levels within an organisation, right up to executive level, where there are “small daily tasks that can be automated, such as scheduling, logging onto systems and creating reports”, adds Mee.
Automation can free employees to focus on higher value work
By automating some or all of these repetitive tasks, employees at whatever level of the organisation are freed up to focus on meaningful work that is creative, collaborative and strategic, something that will not only help them feel more engaged, but also benefit the organisation.
“Automation can free people to do more engaging, rewarding and higher value work,” says Mee, highlighting that 68% of global workers believe automation will make them more productive and 60% of executives agree that automation will enable people to focus on more strategic work. “Importantly, 57% of executives also say that automation increases employee engagement, all important factors to achieving business objectives.”
These aren’t the only benefits, however. One of the problems with employees doing some of these repetitive tasks manually is that “people are fallible and make mistakes”, says Mee, whereas automation boosts accuracy and reduces manual errors by 57%, according to Forrester Research. Compliance is also improved, according to 92% of global organisations.
Repetitive tasks that can be automated
Any repetitive process can be automated, Mee explains, from paying invoices to dealing with enquiries, or authorising documents and managing insurance claims. “The process will vary from business to business, but office workers have identified and created software robots to assist with thousands of common tasks they want automated.”
These include inputting data or creating data sets, a time-consuming task that 59% of those surveyed globally said was the task they would most like to automate, with scheduling of calls and meetings (57%) and sending template or reminder emails (60%) also top of the automation list. Far fewer believed, however, that tasks such as liaising with their team or customers could be automated, illustrating the higher value of such tasks.
“By employing software robots to undertake such tasks, they can be handled much more quickly,” adds Mee pointing to OTP Bank Romania, which during the pandemic used an automation to process requests to postpone bank loan instalments. “This reduced the processing time of a single request from 10 minutes to 20 seconds, allowing the bank to cope with a 125% increase in the number of calls received by call centre agents.”
Mee says: “Automation accelerates digital transformation, according to 63% of global executives. It also drives major cost savings and improves business metrics, and because software robots can ramp-up quickly to meet spikes in demand, it improves resilience.
Five business areas that can be automated
Mee outlines five business areas where automation can really make a difference.
- Contact centres Whether a customer seeks help online, in-store or with an agent, the entire customer service journey can be automated – from initial interaction to reaching a satisfying outcome
- Finance and accounting Automation enables firms to manage tasks such as invoice processing, ensuring accuracy and preventing mistakes
- Human resources Automations can be used across the HR team to manage things like payroll, assessing job candidates, and on-boarding
- IT IT teams are often swamped in daily activity like on-boarding or off-boarding employees. Deploying virtual machines, provisioning, configuring, and maintaining infrastructure. These tasks are ideal for automation
- Legal There are many important administrative tasks undertaken by legal teams that can be automated. Often, legal professionals are creating their own robots to help them manage this work. In legal and compliance processes, that means attorneys and paralegals can respond more quickly to increasing demands from clients and internal stakeholders. Robots don’t store data, and the data they use is encrypted in transit and at rest, which improves risk profiling and compliance.
“To embark on an automation journey, organisations need to create a Centre of Excellence in which technical expertise is fostered,” explains Mee. “This group of experts can begin automating processes quickly to show return on investment and gain buy-in. This effort leads to greater interest from within the organisation, which often kick-starts a strategic focus on embedding automation.”