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The biggest obstacle that gets in the way of business agility for IT leaders is back-end legacy systems and homegrown solutions that are connected through point-to-point integrations. This ugly, brittle mess of integrations is expensive to maintain and difficult to modify. In fact, many IT teams spend up to 80% of their time on integrating, rather than focusing on innovating. The negative effects on business agility and efficiency can only be imagined. And this is only set to continue, as digitization continues to accelerate and the number of business initiatives grows.

So how can organizations accelerate digital innovation? First, increase the speed of project delivery. Second, become agile in order to adapt to changing business requirements over time. In a recent customer spotlight, Dŵr Cymru from Welsh Water, a not-for-profit company supplying drinking water and wastewater services to three million customers in the UK, explained how they tackled this challenge. 

APIs as the glue between data and services 

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Welsh Water opted for API-led connectivity as an approach for connecting and exposing assets. API-led connectivity is a methodical way to connect data to applications through reusable and purposeful APIs. These APIs are developed to play a specific role – unlocking data from systems, composing data into processes, or delivering an experience. 

Before, the company was connecting it’s systems via point-to-point integration. With this new approach, APIs became the glue between Welsh Water’s customer service and the data in it’s back-office systems — this enabled automation for many of the organization’s manual service processes. Now, Welsh Water’s data exists in one digital space. Every asset operates as a building block that represents unique business capabilities that Welsh Water teams can compose easily into connected experiences. 

Automate, digitize, and transform customer services

Let’s take a closer look at a key initiative at Welsh Water: the digitization of its customer services. Historically, at Welsh Water — both customers and service agents performed inefficient manual processes to complete a service request. A customer would submit an online form, which was then processed manually by an employee in the back-office systems. Common service requests received include everything from setting up a direct debit to submitting a meter reading.

The company wanted to automate, digitize, and transform the customer services across its various channels — such as web and telephone requests. Using APIs the company automated and orchestrated a majority of these customer transactions. 

Welsh Water rebuilt each of these services using agile methodology, each new service was tested with real customers, and the newly automated processes were improved based on their feedback. These new automated and connected experiences have increased the efficiency at Welsh Water, resulting in an improvement in their customer satisfaction rating. Now, 96% of customers rate digital services from Welsh Water as ‘good’ or ‘excellent.’

A better response in times of crisis 

This year, the company was not only impacted by COVID-19, Welsh Water was also impacted by terrible weather. API-led connectivity helped the organization respond quickly and effectively to change and crises. 

In response to these rapid changes, the company used the reusable building blocks exposed by APIs to quickly orchestrate the services related to ‘operational contacts.’ Any impact on water supply reported by a customer is now processed in real-time through the systems of Welsh Water, and the company is able to provide real-time feedback to the customer. Both the pandemic and the weather disruptions sharpened their focus. It became more important than ever to get customer services right in worrying times. An API-led approach and MuleSoft made this possible.

Watch the Customer Spotlight Webinar with Welsh Water.

To learn more about API-led connectivity we can recommend the whitepaper ‘API-led connectivity: Building a future-proof IT infrastructure for long-term resilience at scale.’