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Harnessing the power of artificial intelligence can help you increase productivity, improve forecasting and maximise efficiency
Securing a healthy return on capital while driving growth is a key challenge for all business leaders. Cutting costs provides an obvious route to achieving this aim. But improvements in operating profit need to be smart and sticky to be sustainable and yield long-term growth. AI can provide a range of ways to increase productivity, improve forecasting, cut downtime and plug costly leakages across production, supply chain, procurement, customer care and administrative overheads.
Software robots from the likes of Blue Prism, Automation Anywhere, Pega and UiPath perform routine tasks such as accessing applications, data entry and calculations. They mimic activities done by humans, so legacy IT systems do not need to be changed.
Many companies have installed software robots to achieve quick savings. But in many cases, benefits have proved elusive. Organisations are structured around processes rather than tasks, and those processes are spread far and wide: they are fragmented. Hence organisations face the challenge of translating the automation of tasks into savings.
The companies that have succeeded in capturing the full potential of AI technologies have taken a holistic approach rather than pursuing robotics alone. They have reimagined processes and organisational structure and deployed a variety of technologies such as machine learning and cognitive applications in addition to robotics in an integrated way. For these companies, applying AI technologies alongside process streamlining and digitisation has brought big savings – sometimes as great as 30–70%. Savings of this size have even made it possible to move some activities back from offshore locations. And faster processes have improved the customer experience.
The companies that have succeeded in capturing the full potential of AI technologies have taken a holistic approach rather than pursuing robotics alone.
Looking at how motor insurance claims are processed gives a powerful illustration of how applying the whole suite of AI technologies creates impact:
Over the past two decades, companies have adopted lean and automation to reduce waste and boost efficiency. As further improvements were becoming tougher to achieve, AI has turned up as the white knight allowing them to move to the next level of productivity.
Machine learning and robotics already allow companies in retail, packaged consumer goods and high-tech sectors to transform their supply chains into a source of competitive advantage. Companies are using AI to accurately forecast customer demand for vast numbers of different items. They then complement the improved forecast with flexible and efficient supply. They have automated warehouse processes using robots for picking and packing; and made transport for supplies and delivery responsive to real-time information such as weather forecasts and traffic flow.
German e-commerce merchant Otto can now predict with 90% accuracy what will be sold over the next 30 days, reducing its surplus stock by a fifth and product returns by more than two million items a year. Algorithms look not only at historical sales, but also take account of advertising campaigns, store opening times, local weather and holidays to predict demand for individual lines from each outlet.
Amazon uses Kiva robots which bring packages to human workers standing on platforms. Amazon has increased inventory capacity by 50% and reduced operational costs by 20%.
AI can help companies meet customers’ ever-rising expectations for personalised service and for getting what they want straight away.
Purchased goods and services typically make up 60-80% of a product’s cost. AI can arm purchasing managers with information and insights to secure better deals. But procurement data in many companies is uncleaned, unclassified by categories of spend and spread across different systems. However, Coupa software uses machine learning to automate the clean-up and classification of information. It claims to have analysed more than $1.3 trillion of spending. Businesses can further reduce procurement costs by plugging leakages arising from non-compliance and inefficiency by automating order management, especially for long-tail spend. Typical leakage is 3-4% which is equivalent to £180-£240 million on a £6 billion spend.
There is vast scope for using AI to reimagine administrative processes. Imagine a system that takes a picture of a receipt and uses optical character recognition to read the text, with machine learning then identifying the sum, date, currency and type of expense: put it together and it could create an expense entry.
As human resource departments step up from their traditional service role to strategic business partner responsibilities, they can take a cue from Michael Lewis’s book Moneyball to derive data-driven insights about talent.
Abhijit Akerkar (MBA2008) is Head of Applied Sciences, Business Integration, Lloyds Banking Group
What every CEO needs to know about AI. Part three: managing risk
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