Solve complex business problems
Devbridge builds bespoke software that delivers measurable results for our clients. We primarily build custom products, seldom implementing off-the-shelf solutions in addition to custom work. We build greenfield products with the newest technologies, we take over failed implementations from other vendors, we modernize old legacy platforms.
In addition to product development, we partner with businesses and provide them with strategy around research, definition of opportunities fueled by technology. These opportunities often lead to organizational change - the need to restructure IT to a Product organization and beyond.
Here are some of the most common categories of work:
Information Technology has historically existed as a support role. A separate department tasked with projects that needed to be built for business. Due to growing capabilities of digital, shifting services landscape, and the unique skill set needed for product development this approach is no longer a viable option.
Digital capabilities are transforming industries and businesses and our clients discover the need to shift to a product-centric mindset and organizational structure. Incredible value can be unlocked through a nimble, iterative product delivery model that focuses on business outcomes instead of activity.
Our clients use Service Design to find gaps and opportunities in their customers' experience. Service Design is a methodology for mapping the full lifecycle of a particular service provided by the business. The blueprint produced in this workshop identifies all touchpoints of the customer, as well as all impacted processes and departments in the business. Pain points, inefficiencies, and opportunities are identified and a starting point for product development is chosen. Multidisciplinary agile teams quickly iterate and ship working software to market. This working model allows the team to take complete ownership of product outcomes - from research to prototyping, to design, and production readiness. No excuses, just working software in production.
Product metrics are established from day one to gauge effectiveness of investment and determine future roadmap. Product analytics help teams make informed decisions about the product roadmap. The tools available today can capture top-level metrics such as adoption, granular insight around feature usability, high friction application areas that are demotivating customers, and many others. Implementing analytics is often de-prioritized by business in favor of features. We have taken the opposite approach and mandate implementation of analytics as means to determine which features will generate the best ROI.
Products are more than a collection of features, they’re the face of the company and the workbench of its team. Our approach finds the intersection of efficient and effective, producing high-quality experiences that stand out and improve the bottom line.
Features alone do not create a competitive advantage. Chasing release after release without taking the greater system into account leads to a build-up of product debt, making it more expensive and time-consuming to adapt. Customers become weighed down by a product optimized for business processes rather than the tasks they set out to complete. Service design builds products that address problems, with metrics baked in from the start to inform priority and direction.
It is important to understand the system to identify opportunities for development. User-centered design helps create a great experience for the user, but only if the entire system is taken into account. Service design seeks to map out what happens upstream from the user and how it impacts them, what will happen downstream from their actions to complete the task, and external factors that may impact their ability to use the product. When each is understood, the unique risks and opportunities in each can be identified and built for.
We find measurable moments to demonstrate business value. Being data-informed is the path to successful delivery, and through service design, we are able to identify the moments in the process that are most meaningful to measure. We identify the baseline early, build analytics into the product, and track progress week over week, using this to inform future release priority.
The best products exist at the intersection of user value and business need. Take one without the other and the solution is incomplete. The product represents the experience someone has with the business, or working within the business. We build for business outcomes and design for the people using the product.
To maximize the ROI from technology the enterprise needs to become product-centric. Such an organization has the culture, structure, and tooling that enables nimble response to market shifts, meaningful implementations of technology, as well as an evergreen strategy for maintaining existing applications. To become agile and scalable, leaders must facilitate an organizational shift.
A mature engineering organization requires a set of sub-disciplines that enable agile teams to perform at maximum capacity. These disciplines are product design, product management, DevOps, data design, testing strategy, security, code quality, source control, scalability, performance, and monitoring. Our objective is to establish a mature engineering practice for the client that will produce evergreen software.
Automation through DevOps lowers maintenance costs, decrease defects and the organization is then able to predictably respond to market needs with bespoke software.
We’ve found that organizational structure implies team effectiveness, also known as Conway’s law. Devbridge facilitates organizational change for the enterprise to adopt the product mindset. Instead of having siloed business and technology teams, we build cross-functional product teams under the guidance of a Chief Product Officer. Advanced funding models allow companies to maximize the value of agile while maintaining predictable delivery and outcomes from investment. Furthermore, a mature infrastructure is a core requirement necessary to transform into a product org. Otherwise, most product ideas lose traction beyond the proof of concept stage and fizzle out—hindered by unpredictable environments, slow deployments, and manual provisioning requests.
Great products are not built in a vacuum. They are influenced by user research data and defined in a collaborative workshop between domain experts and a cross-functional product team. Our training program tracks split to enable leaders as well as front-line teams. We educate teams on product management, product design, as well as engineering maturity.
We have cleaned up the data, built the necessary services to read and write to our “single source of truth,” and can now rebuild the outdated green-screen legacy applications. To be fair, I’m simplifying the actual state of affairs . . . by a lot.
Modernizing large legacy applications is one of the toughest engagement types because it often requires feature parity between the old and the new. Capturing realistic scope is almost impossible because of ancient business logic buried deep in legacy code. Release strategy is often restrictive as an MVP does not carry enough functionality to warrant execution of the old platform behind the shed.
And yet these platforms are the foundation on which our whole economy relies. From power generation to health care, to financial services, all industries are burdened by and depend on software that has not aged well. Older software can be expensive to maintain and difficult to update. Original code lacking mobile responsiveness or compatibility coupled with years of one-off features water down the original intent, rendering apps useless. Dated UX gives users a clunky experience. Lack of accessibility and modern features could further alienate users—and result in litigation—costing even more. Meanwhile, the competition is swooping in, shipping new products to market, and snagging users.
Technical discovery and definition help establish a manageable roadmap. Technical feasibility and discovery assess the existing software from a perspective of complexity, maintainability, technical debt, process maturity, testing strategy, scalability, and deployability. The goals of the discovery process are to a) define steps necessary prior to start of development (e.g. environment prep) and b) assess risks associated with the state of codebase (e.g. debt, design flaws, etc.). This informs teams on how to approach the modernization effort - one size does not fit all.
We prioritize working software over feature parity. To reduce risk, the immediate focus is to create a deployable product. This is incredibly important to a) discover actual, unbiased business uses cases, b) build alignment with stakeholders of the application, and c) inform overall roadmap based on velocity of the individual component release. In other words, the legacy system needs to be divided and conquered.
We map how software should cater to the business, not the other way around. Legacy systems often force the business to invent processes to work around limitations of outdated technology. We don’t take “feature parity” at face value and involve the business in the experience design of the modernized application. Outcomes over activity.
Taking a long-standing, successful product into a new era is a critical step for a company. It starts with developing a smart, thorough plan and executing it. While rebuilding takes time, making this move can significantly alter the future for organizations.
This is enterprise “digital transformation” work—a phrase I can’t write without rolling my eyes. To us, it’s not all that transformative. It’s more like common sense. “You’re telling me you rekey all insurance applications manually? Twice?” Large enterprises, often burdened by the above legacy systems, have a myriad of these gems in their workflow. From a bank’s paper-based customer onboarding to a health-care scheduling system based in Excel—workflow digitization efforts identify efficiency opportunities in existing user flows and introduce software as a means of improving day-to-day productivity and accuracy.
This takes many forms. It could mean transitioning contract signing from paper to mobile, moving a hardcoded underwriting engine to a visual rules engine, or developing a digital onboarding workflow.
Digital transformation is a process shift that leverages software product to
- dramatically lower operating costs; and/or
- dramatically improve output.
DT improves turbine uptime through machine learning and predictive analytics and doubles the work a field service engineer can accomplish through automation of a paper process. While a slow-moving enterprise can’t just hyperdrive into a transformation, to transform anything an organization needs to sort out key fundamentals.
Before we gravitate toward emerging technologies, leaders must take care to pay back the fundamental technical debt. We look at the building blocks necessary to transition an organization into a product-capable entity. These include but are not limited to design research, accessibility, security and performance testing, analytics implementation, and DevOps.
These fundamentals allow a company to become product-centric and capable of nimble, meaningful implementations of technology. They pave the way for speed to market.
Enterprises are often struggling with information silos, lacking confidence to make decisions based on difficult to access data. We work to define the architecture and data models that support a single source of truth reality, a way for our clients to guide the business with data-driven decisions.
Companies are crunching more raw data than ever before. Traditional IT systems that are backed by relational databases were gradually augmented with NoSQL-based solutions, data streaming, and raw machine data. As data becomes abundant, the strategy shifts towards ability to store and use. Without proper planning and implementation, additional raw data does not lead to insights. On the contrary - correlation and causation between data obesity and information oblivion are, sadly, proven practically. A shift in data handling strategy needs to be made to maintain agility and data decoupling.
Our approach is to achieve near real-time reporting and visualization using data streaming.
A company will spend 60-80% of all data science budget on plumbing, cleansing, orchestration, and monitoring, with only a fraction left to build actual data models and finally enhance business decisions. Devbridge brings expertise in “master data” solutions, designing data ingestion and processing flows, visualizing result data, and performing deployment and monitoring. Our clients can focus on AI/ML components that are, undeniably, the most valuable IP that drives business value.
Lengthy Data Warehouse application projects utilizing Enterprise Canonical Data Models go against our Agile and DevOps fundamentals. Instead, we start with an independent data mart which is derived from a selected business application. We establish Near Real-Time reporting, dashboards, and alerting. We build efficient data pipes and dedicated search-optimized databases to normalize resource usage of client-facing applications. We push main business events to Data Streaming platform and receive real-time alerts based on lightweight business rules.
Being an independent technology partner, Devbridge is unbiased in selection of cloud-based providers, data storage technologies, or desktop visualization tools. Having analyzed individual requirements, restrictions, and future capabilities, we offer a technical solution that ranges from pay-as-you-go publish-subscribe app on the cloud to on-premise, high-load containerized processing powerhouse with Apache Kafka.
Some clients we work with fall further outside our typical scope. Every now and then a debate ensues over whether the work we do for them is good. In a typical engagement, we have ownership of the product. Perceived or actual, this control makes us feel significant—important even. But with some clients, we find ourselves at the discretion of their product managers, which can mean we get our butts kicked because we overpromised and weren’t able to meet expectations. You want my personal opinion? That’s the best work. Here’s why.
No client is perfect, but there is one that comes to mind that has most certainly pushed us out of our comfort zone. The number of testers per team? Too few. Escaped defects? Too many. Working within the constraints that they force on us makes us change how we operate, and usually for the better. Building up competence and consistency over time allows us to exert influence.
It’s important I stress this: Whenever you feel uncomfortable and want to avoid an issue, it’s probably a good indication that you need to lean in and push even harder. This applies to account management, influence with the client, personal conflicts outside work, and many other areas.
The above is one of many examples I can give of work that teams find frustrating, but I urge you to shift your perspective. I like to look at work in terms of (a) challenge, (b) impact, and (c) results. Ideally, all three align. If they do not, we have to figure out what we need to do to achieve alignment.