In 1980s Liverpool, the Unilever soap factory had a problem. A nozzle on their laundry detergent machine was blocked, rendering the whole machine non-functional. It wasn’t the first time, either. It happened constantly and every time it did, production was completely halted.
An update was required. So, they got in physicists, chemists and mathematicians - experts who understood fluid dynamics - and asked them to calculate the optimal design for the nozzle. After endless discussions, calculations and meetings, they unveiled their new design.
It didn’t work. They failed. Their time was wasted.
The way Unilever eventually solved the problem was with a radically different approach, inspired by evolution itself*. The biologists charged with designing a better nozzle started with the original design. They created 10 variants on that design, and measured which one performed best. Then they took that one, created 10 more variants on it and repeated the process. With every stage of testing, they were making progress and improving the design.
By the 46th round of testing, they had designed a nozzle that worked brilliantly.
Why? Because by shortening the development cycle, they were able to focus their efforts on the path that showed real results. The biologists got through 46 development cycles in the time it took the mathematicians to get through 1.
Technology improves fastest when we shorten development cycles and adopt Agile modes of work. We open ourselves to possibilities we might not have originally envisioned, and we make our solutions the very best they can be.
Moreover, we use our time and resources more effectively. We discover sooner whether we’re wasting our efforts and we keep ourselves in check.
For instance, when the DVELP team worked with Marks & Spencer to introduce intent-based routing to their contact centre, we started with a Minimum Viable Product (MVP). Following the MVP, we built out further functionality iteratively. The result was a solution that worked. We didn’t waste any time on redundant functionality because, like Unilever’s biologists, we kept ourselves in check with real results. You can read more about our M&S project here.
Where previous progress has been prohibited by slow-moving hardware, new technology from companies like Twilio and Google Cloud enables our team to offer contact centre innovation at a revolutionary pace. For example, when we work with Flex, Twilio’s contact centre platform, we go live with agents on a basic functionality version as soon as possible, whilst experimenting with new functionality powered by Google Cloud AI, such as agent assist. Thereon we develop features and functionality iteratively, focusing on what makes a meaningful difference to agents and customers. This is possible because we move control of a business’ telephony from outdated legacy providers to software development teams.
This means that creating new routing rules, setting up new agents or adding self-serve options can all be implemented by internal teams. This removal of reliance on legacy providers means no more long wait times for professional services. You can make changes when you see the need for it, as a result of agent feedback or customer demand.
This change to an iterative, responsive culture becomes the new normal for your contact centre and reduces risk. In direct contrast, legacy contact centres based on hardware that require huge upfront investments of time, stakeholder processes and business analysis to build to a predefined scope that would become a barrier, rather than an enabler, to your customer service operation.
Our clients understand that technology and consumer preferences are closely aligned and to deliver against their expectations, they need new technology and new process to keep pace.
*Syed, M. (2015) Black Box Thinking: Why Most People Never Learn from Their Mistakes – But Some Do, New York: Random House.