Intelligent automation is a business imperative: not just making organisations more efficient but enriching customer and employee experience – not to mention helping to identify new business strategies. To successfully transform your organisational culture to one that embraces automation, there are five key steps (and a few basic tenets) to ensure you get the most from IA.
01 February 2022 • 4 min read
Intelligent automation, or IA, is a combination of software technologies that automate or augment knowledge work to improve speed, efficiency, or accuracy. Its goal is to achieve improved business outcomes through automated processes. And its benefits are diverse and far-reaching.
IA is a business imperative. It makes your company’s processes more efficient, improves your customers’ and employees’ experience, and helps you find new business strategies.
Companies often lose customers due to frustrating and unresponsive customer services. IA can help by automatically routing queries to the right person, responding to simple queries using chatbots (to free up human agents for the more complex ones), and sharing information between agents and systems to provide a seamless, omnichannel customer service experience. For example, the hotel chain Wyndham uses a robotic process guidance solution to pre-fill agents’ screens with real-time instructions and customer data to help them in discussions with clients.
You can also use sentiment analysis to monitor perception of your brand on social media and respond accordingly, or use data analytics to improve products and marketing campaigns, tailoring them based on customer demographics and purchasing behaviour (as Netflix has done – their personalised recommendation algorithm has saved an estimated $1 billion in cancelled subscriptions).
Businesses that seek to improve the experience for employees are four times more profitable.
Businesses that seek to improve the experience for employees are four times more profitable. IA can improve morale and reduce employee turnover by freeing workers from the most tedious and repetitive aspects of their jobs, allowing them to spend more time on creative or relational tasks that are more fulfilling and higher-value. IA can also reduce workload and pressure by speeding up processes and automating time-consuming tasks. One hotel chain with over 20,000 client interactions per day reduced employee turnover by 70%, and improved service quality by 40%, by using a cognitive agent.
By automating and streamlining business processes – reducing or removing the need for human intervention – IA makes organisations much more efficient. It can also improve accuracy, reduce losses due to administrative errors, and improve transparency and compliance by logging its actions.
Finally, IA can reduce losses due to fraud, both because automated processes are more resilient to deception than human ones, and because insight from machine learning can detect suspicious transaction patterns to flag for investigation.
Intelligent automation technology can be divided into four main capabilities: vision, language, thinking and learning, and execution. Some of the most powerful IA applications link two or more of these capabilities together.
Computer vision is the ability to detect and interpret information from images or video footage. It’s used in intelligent character recognition, to scan documents and identify information – for example, extracting payees and amounts from a batch of invoices. Other applications include self-driving cars, medical diagnostics (detecting disease from scans and X-rays), retail store automation (using camera footage to automate check-out and inventory management), and biometrics (such as facial recognition).
Computers are rapidly becoming better at understanding and generating human language, using statistical models rather than a set of rules. This capability is used to power intelligent chatbots, to transcribe speech to text, to automatically translate or summarise documents, or for sentiment analysis: inferring emotions and opinions from written text.
Thinking and learning
The thinking and learning capability is about analysing data to create insights, make predictions, and support decision-making. Applications include detecting patterns of transactions or insurance claims that suggest possible fraud, assessing loan applicants for credit risk, or analysing sales data to identify the highest-impact promotions and marketing campaigns.
This is when software interacts with digital systems and performs tasks using them, such as logging in, filling forms, or routing data between systems. The execution capability includes robotic process automation (RPA), which can automate the mouse clicks and text entry performed by a human, and low-code platforms, which enable users to build automated processes without needing coding skills.
The execution capability connects the other capabilities together into a touchless automated pipeline. For example, it could collect data that the vision capability has scanned from documents or images, convert it for the thinking and learning capability to analyse and generate insights, and automatically update a database or scheduling programme based on these insights.
Start small, think big, and scale fast.
Based on helping hundreds of companies transition to IA, I’ve identified these key steps for ensuring your IA transformation is successful.
Identify and prioritise use cases
Identify IA use cases across the largest scope of divisions or entities – the broader the scope, the higher the potential benefits and the capacity to invest. Prioritise these based on feasibility and impact. Start small, think big, and scale fast. Plan an achievable but high-impact pilot so that you can demonstrate the benefits of IA to colleagues.
Build the business case
Calculate the estimated costs and benefits to build a business case and create buy-in across your organisation.
Get top management support
The IA transformation is more than just a technology project: it’s a deep restructuring of the whole business, involving people and processes as much as technology. It must be supported and sponsored by the top levels of management. They need to set the vision and release the financial and human resources.
Build capabilities early
Assemble the right talent very early in the process, including business and operations as well as IT. Identify internal candidates, with knowledge of your business, who are interested in IA and train them up. Make sure the IT infrastructure is in place in advance.
Build your roadmap
Use the insights gathered from the previous steps to build an agile, iterative roadmap, including launch, preparation, scaling, and change management.
Show workers the benefits that IA offers them personally, so they welcome it as a tool to augment their capabilities and save them time, not resent it as a threat to their jobs.
Develop a company culture that embraces automation. Show workers the benefits that IA offers them personally, so they welcome it as a tool to augment their capabilities and save them time, not resent it as a threat to their jobs. Encourage workers to identify opportunities for automation in their day-to-day work, and you’ll be able to get the most from intelligent automation, making the lives of everyone – from customers to staff to shareholders – happier, easier and more prosperous.
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