It goes without saying that gen AI will dominate strategic conversations this year, as organizations look to take advantage of last year’s breakthrough technology. As Capgemini suggests in its Top 5 Tech Trends to Watch in 2024 report, gen AI will live up to the hype, especially with the development of smaller, more targeted, cost-efficient Large Language Models. Automation will filter across departments and roles, changing personal and productivity capabilities and goals. As a result, many organizations will see gen AI as a core focus for transformation, and the new technology trend that can deliver new opportunities, increased margins and growth.
To a large extent that will be true but it’s premature to assume that gen AI will deliver substantial benefit in 2024. After all, AI works best with data and gen AI is only optimal when trained with the right data. In my experience, most business leaders want to know what will help them in the here and now, not just the long term.
As with any modern technology shift, there is a fundamental requirement that an organization is joined-up with its strategic thinking but more importantly, with its data. It’s a constant challenge for any transforming business – how to ensure departments can interrelate and feed the organization with the sort of intelligence that improves overall performance.
The challenge on this front is that different departments and different roles each demand different flavors of data. There is no one-size-fits all, but contextualized data comes pretty close. MIT professor Alan Kay is credited with saying ‘A change of perspective is worth 80 IQ points”, illustrating the point that the more data you have about what’s going on, the better your analysis can be.
Data is more composable now than ever with end-to-end processes across a manufacturer’s enterprise, making contextualized insights possible. Imagine having product and customer intelligence at every stage of a product’s lifecycle? That would surely be a foundation for delivering real world insight and significantly impact and elevate decision making.
There was a time when service and asset data was separate and divorced from other functions. Service was historically the beige after-thought and the poor relation to sales. That’s no longer the case as organizations have modernized both their thinking and infrastructure.
While many organizations have already transformed their service teams – focusing primarily on optimization of service, reducing costs and improving resolution times – there is now an increasing realization that data derived from the service function, that often represents the most up-to-date status of the asset, has multiple benefits to the business. In short, this contextualized data has a richness that impacts organizations in multiple ways. It can minimize service costs and increase productivity, increase revenue, improve customer experience and retention, and improve asset lifetime value and performance. It can also support broader enterprise initiatives around quality, reliability, and sustainability.
Why everybody wins
At the heart of this is products and people. As Deloitte suggested in its report Next Generation Customer Service: The Future of Field Service, to transform to next generation field service, businesses need a 360-degree view of customers and assets but that could also be applied to the broader business. Unifying organizations, bringing departments together and collaborating regardless of location, demands centralized and easily accessed service and customer data.
Understanding customers, the equipment assets they buy and how they use them at every point of the journey is incredibly valuable to every department.
How do CEOs increase overall performance, shareholder value and deliver on strategic goals? How do sales teams close more opportunities and increase the value of each sale? How do customer success teams reduce customer churn and increase customer experiences? How do marketing teams increase lead quality and conversion rates? Each of these personas and departments has its own challenges but what links them all together is data – contextualized asset data that provides intelligence on how assets are deployed and used, as well as customers’ needs and future intentions.
A major component of any field service operations day-to-day business is the data that is used in the variety of operational processes. Field service engineers, dispatchers and managers rely on and collect valuable data direct from source and ensure its accuracy, whether that’s product status and performance, contracts, contacts, location or account details.
This data, which can be curated and fed into an organizations data system, has the potential to provide accurate intelligence across the organization. It touches and enhances other data sources such as CRM, ERP, parts, logistics and supply chain, HR, compliance and sales – creating a digital thread of insight and intelligence, and ultimately delivering better service for customers.
Feeding future growth
As power management and automation global leader Schneider Electric reveals, harnessing this contextualized data from service operations can have wide reaching benefits. Schneider has implemented a digital strategy to support and maintain a complex legacy customer base, while extending its sales focus to include the tracking and identifying of additional service revenue opportunities within that base. Over two years, Schneider Electric enjoyed significant results, including an 8% increase in won opportunities, a 3% increase in first-time fix rates and an additional €65m in upsell and cross sell revenue.
This is just one example of a business that is utilizing its asset and customer data to feed other areas of the organization. It underpins relationships with customers and ensures that decision makers, at all levels, have access to the latest data. For CEOs, looking to steer organizations through turbulent waters and towards a more automated future, this is invaluable. The ability to see, in real-time, how assets are performing, and project customer and asset trends drives planning. Through engagement models that map customer needs, leaders are leveraging data and insights, to inject agility into the organization, as well as confidently make decisions and drive revenue.
For example, while Service Sales Managers are responsible for working with customers after the product has been sold, in the face of constantly changing customer and market conditions, sales and service must take a closer look at the entire value chain and improve processes, innovations and the access to joint data and information. Profitability and growth drivers lie in service, which is why it’s necessary for sales and service to act in a much more process-oriented and interlocked manner. This allows new service business models to develop and achieve stronger customer loyalty, to maximize revenue performance and to improve competitive win rate.
This type of approach also helps generate additional revenue opportunities, meet service upsell sales targets, improve customer retention, help articulate financial and business value of the relationship to their customers, as well as the creation of new service offerings to meet customer needs. Service data also provides clear visibility into contract profitability to meet and exceed margins. Accelerating revenue by increasing up-sell, cross-sell, conversion and attach rates, not only drives growth but also increases Service Contract Renewals, contract profitability and margin.
It’s at this point that organizations can then start to explore and utilize the latest technologies, such as gen AI. Contextualization is key to modern business thinking and fundamental to digital transformation. Business growth, through improved sales, better designed products, happier customers and a more aligned, efficient organization can be fed directly with service data from your equipment assets. This is the new fuel that will ultimately drive the organizations of today and tomorrow.
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