The Product Engineering Paradigm: Moving from idea to production at the speed of customer expectation

With all the acronyms in the digital world, let’s talk about one more: VUCA. The term itself is not new, but it describes the challenges businesses are facing today. Volatility, Uncertainty, Complexity and Ambiguity. The digital world has heightened customer expectations, which in turn has shortened the life span of software development activities and raised the prevalence of these four conditions.

What used to take a year and a half in a classic software development model has shrunk to weeks if not days driven by  digital customer expectations. Years ago, businesses had the luxury of spending valuable time in product development cycles, which lasted 12 to 18 months on average. Today, moving at that pace will result in wasted time and irrelevant products at the end of a long journey.

In order to move at the speed necessary, we look at successful digital native companies that have mastered the art of product engineering. No longer are services ideated extensively and a detailed road map put in place to take them to market. Instead, new products are developed in small, agile, incremental shifts.  For example, Facebook has divided its entire customer experience into sections where smaller teams have end-to-end responsibility, from user experience design to testing to application development. This results in parallel teams that each ‘own’ their product. Amazon, an early adopter of DevOps and Product engineering, deployed software in production every 11.6 seconds — and that was in 2013!

In digital native companies, teams are not broken across a software development life cycle. Instead, people work in smaller teams across the entire development stack from UX to Infrastructure. With continuous integration, Agile methodology and DevOps practices, teams become nimble.

Banks have a unique challenge in adopting this paradigm because they must also apply a regulatory and data privacy perspective. Speed and agility cannot and should not compromise regulation and data governance, which are much more rigid for financial institutions.

What is a Product Engineering Paradigm?

The product engineering paradigm, or model, requires banks to completely change their thinking about servicing clients. Banks face a unique challenge of providing a frictionless customer experience during an increasing rate of change while staying grounded in regulatory and data governance in order to maintain the trust they have built with customers. 

The necessary shift to this model is a continuation of the digital transformation journey I have discussed in past articles. For banks, the product engineering paradigm should be considered across the following key characteristics:

  • Innovative and Business Aligned: Product engineering should allow IT teams to foster innovation and be customer centric. It is no longer about building Service Level Agreements (SLA) for IT teams alone, but building SLA’s which service the customer. The business is now a key part of the product engineering team.
  •  Speed in Delivery: By leveraging DevOps practices and Agile methodology, product engineering teams can reduce the speed of delivery of IT programs or products. A common complaint I hear from business users in large institutions is that it takes too much time for IT teams to deliver on their promises.
  • Customer Centric: User Experience has to be at the center of product engineering teams. In a product engineering model, UX is not an after thought and creative teams have to work together with engineering teams to develop customer centric solutions.
  • Hyperconnected Ecosystems: Product Engineers must adopt a re-use approach for faster development efforts in order to deliver on solutions with a quicker pace. It is not about building things in isolation, but rather working in a connected way to deliver fast.
  • Lean, High Quality: Agility is key to product engineering, but not at the cost of quality. Product engineering teams go Agile and change the traditional Software Development Life Cycle (SDLC) models to ensure that quality is a key trait and not something you do at the end of a product. From Pair Programming to automating test scripts and building test scripts during development phase, parameters ensure quality is the responsibility of everyone. Product teams also tend to be leaner, even if virtual, to ensure a more cohesive operational structure.
  • Stable and Secure: The stability of the customer experience and security of user data cannot be compromised for agility. With a continuous development and a 24×7 customer model, digital native companies like Amazon don’t take websites down for maintenance or compromise the security of customer data — even in a fast-paced world. This is arguably even more critical for banks.
  • Test and Learn: Machine Learning and AI have introduced a ‘test and learn’ model to product engineering where the systems mature and adjust as they become self-learning, providing an enriching customer experience without human intervention. The recommendation engine of Netflix is a prime example of a mature learning experience made possible with a product engineering paradigm.

With these characteristics in mind, financial companies are learning from digital native companies and establishing product engineering teams within their organizations.

At a recent conference, CapitalOne talked about how its IT teams are introducing concept of ‘Product Ownership,’ where members of its product engineering discipline take on a role of interacting with business teams. Not only has product engineering brought together technology teams and operations teams, but this demonstrates that it has the potential to connect business leads, marketing, sales, and more in one model.

Lloyds Banking Group’s James McLeod also highlighted how its organization learns from starter banks like Monzo, who deliver debit cards from concept to cash in one month. Before Lloyds’ current engineering transformation program, it took 365 days to get a line of code into production.

Why should financial services C-Suite care about Product Engineering?

The product engineering paradigm offers banks a way to deliver customer centric experiences, agility to quickly adapt to evolving customer needs and relevancy in a hyper competitive environment. CxOs I speak with at large banks also value how working collectively as a single team focused on customer needs is breaking silos across IT, lines of business, marketing and sales within banks. An added bonus of adapting this paradigm is attracting and retaining scarce talent from leading technology companies where product engineering is an expected norm.

Although the path to digital transformation is complex, product engineering paradigm can enable banks to meet customer expectations and overcome volatility, uncertainty, complexity and ambiguity.

The new Citi ad for its mobile app does a great job in explaining simply what product engineering paradigm could mean for banks: ‘designed so you can spend less time on it’.

The Product Engineering Paradigm: Moving from idea to production at the speed of customer expectation

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