The Elephant in the Architecture

why business value should be treated as an architectural attribute

02 March 2020

Photo of Ian Cartwright

Ian Cartwright

Ian Cartwright is a Director at ThoughtWorks, where he applies his two decades of experience as an software architect and hands-on developer to help clients improve their technical capabilities.

We, and our colleagues, are often called on to perform architectural assessments for our clients. When we do this, the architects involved with these systems will talk about the performance of these systems, how resilient they are to faults, and how they are designed to evolve to easily support new capabilities. The elephant that rarely comes up, however, is how different systems contribute to business value, and how this value interacts with these other architectural attributes.

Without understanding value, many architectural decisions become much harder to make. In one example we were asked about adding fault tolerance to a trading system. The cost of doing this, via a hot fail-over to another server, was in the range of tens of thousands of dollars. Could this cost be justified? Our approach to this was to ask about the value of trades that passed through the system and how much revenue this provided to the client. Once they looked into it, and saw the systems were handling millions of dollars a day in trades, adding fault tolerance was trivially easy to justify.

The important thing about this story isn't the fact that the client team neglected to ask about value as part of their decision-making (although there's certainly a lesson in there). The point is that the architecture team didn't know what the value of their systems were, or how different components contributed to the broader business performance. We find this to be a common gap in thinking, when we do these assessments we usually ask to talk to the relevant people from the finance department. That's usually greeted by "why would you want to talk to them?"

In another example we were asked by an insurance company to help break their monolithic system into microservices. They had identified, reasonably, that they wanted to separate them by different product lines (home, personal, car, etc). What they didn't know was what proportion of the company's profits came from each of these product lines, which is an important element in deciding priorities for a breakup like this. The first item to separate probably shouldn't be the most important one in value terms, since the first separation will carry the many risks of doing something for the first time. But once a team is practiced with the separation, then we should get the most valuable product line separated to make it easier to modify and scale.

Examine the architecture with value stream mapping

A good first step in assessing the business value in your architecture is to do a value stream mapping that focuses on the various systems and components in the IT landscape. Business often do some kind of value-stream mapping for business processes, examining how each part of a customer journey impacts revenue and margin, but often once they reach IT the mapping stops and no attempt is made to map value streams through the various systems.

Architects should build on this, allocating similar business measures to the systems that support business processes by extending the mapping into those systems. As well as financial measures, important non-financial measures can also be looked at - to what extent does your customer's ability to check their claim status online affect customer retention? (Such measures are usually more difficult to make, but thinking about how to measure them can often yield important insights.)

With a recent client we conducted such an exercise, starting with customer journeys that described how customers interacted with the client company. We put these steps on the top of a wall in the team room, and then tied each step to the systems and components in the client's IT portfolio. We could then assess how each system contributed to the step in the customer journey and what the effects of a failure might be.

Consider the business value impact of failures

As our first example suggested, there's a particular importance when it comes to assessing consequences of failures. If we want to take measures to improve the resilience of a system, it's good to express it in terms of the value at risk should it fail. One retailer was struggling to justify testing the backup restoration process for their inventory database. With a large backlog of business-visible features needed before the Christmas season, it was hard to prioritize such a technical task. Our suggestion was to ask how the business felt about a database crash on Black Friday: what would be the cost, how quickly would they want the system back up? These questions led to a business-led decision around doing dress-rehearsals for database restores and reducing the time to recovery that otherwise would be buried in IT's work queue.

When doing an assessment of value that would be at risk, it's worth approaching in two complimentary ways. One route is to go top-down, looking at a business function and identifying which software systems support that function. The other is the reverse, starting with a software system, and considering what ramifications a failure here would have.

An important part of analyzing how much value is at risk is recognizing that, since different failures have differently severe consequences, all software components do not need the same levels of resilience. Imagine a failure of a stock management system on Boxing Day (a British equivalent to Black Friday). If that means we can't check stock levels, we either confirm orders we can't fill, or don't take orders - both of which cause a significant loss. However a failure in a fulfillment system might have orders sitting on queue waiting to process, which may lead to delayed deliveries. Business leaders may consider the latter a lesser concern, and thus be prepared to live with lesser resilience for that system. Whatever the particulars, the key is that the level of resilience is a business decision. Similarly with data consistency. When looking at distributed databases, architects often balk at relaxing consistency for availability. But the business cost of double-booking a few hotel rooms may be much less worrying than not taking bookings at all. The trade off between consistency and availability, enshrined in the CAP theorem, is a business decision, not a technical one.

Cross-functional requirements should be justified by business value

A theme here is that we shouldn't just be assessing the value of features, but also of system characteristics that are often categorized as cross-functional requirements (our preferred name for non-functional requirements, or "ilities"). If we want our systems to adhere to some technical standard, then we need to understand what value is lost by failing to do that - and communicate that value to non-technical stakeholders. Assessing value for CFRs is often difficult, and many technologists shy away from the resulting debate. But failing to do this does more harm than just the risk of over-investing in low-value technology. It also erects a real barrier to the collaboration between technologists and their users.

Understanding value should inform decisions about the flexibility of components. One client had a payment processing component that was programmed to work with a particular payment processing company. They wanted it to be easily configurable so they could adjust it quickly should the payment processor change. Two broad options existed. One would hard-code the interaction with the payment provider's system in the payment processing component, while the other option made all such interactions be configurable. The configurable option would allow the payment provider to be changed by altering a configuration file in a few days. As is usually the case, however, such configurablity would add complexity to the component's code that would increase the cost of any other changes. This is a common trade-off with configurablity - you ease changes in the configurable bits at a cost of harder changes elsewhere. The vital piece of business context here was that the hard part in changing a payment provider was actually negotiating a new legal contract - an exercise that usually took over a year to do. So configuring the provider information here wasn't worth it, as modifying a non-configurable component was still much quicker than legal negotiations.

Business value implies CFRs vary by component

The last two examples both illustrate that having a "one size fits all" approach to things like resilience and flexability can be unhelpful and wasteful. Several years ago we worked with an organisation that had decided to impose a blanket "five nines" availability requirement, amazingly they even applied this to the sandwich ordering system used by staff to reserve their favourite lunchtime snack. We've found agreeing different tiers of service with the business can be very useful, for example does loss of a service immediately impact customer experince or revenue, or can we afford for it to be down for a few hours while a database is restored?

Another issue that can be highlighted by understanding how systems support business value is where a single component has to support multiple different value flows and levels of reliablilty. This is common in monolithic components where multiple different business processes are supported and can be an important motivation for breaking things apart, for example allowing us to only pay the premium for high availability when justified by the corresponding business value

Use monitoring to assess business value

We're big fans of using rich monitoring to get a better understanding of how systems behave, something that's particularly important with the growing complexity of increasingly distributed systems. Such monitoring is often focused on system health, supporting QA in production. But we can also use this kind of monitoring to assess the contribution of systems to business value - such as determining how much sales revenue passes through a particular component. One retail client found that monitoring queue lengths and message rates on their mainframe could be a good proxy measure for revenue taken in each of their shops, while not accurate making this available to the business stakeholders let them spot issues that monitoring from a purely technical perspective might have missed. Another client was able to derive an accurate revenue measure for every transaction on their web site and they displayed this minute by minute on screens around their offices. Over time far more attention was paid to these than the screens showing CPU, memory and other technical measures.

One might argue that gathering such data isn't part of understanding the system's behavior, but we would assert that this is vital intelligence in understanding the contribution software components make to the business. As more systems get hosted on clouds, we can see bills generated for individual FaaS functions. If we can get costs to this granularity, we should also strive to gather data on benefits too.

Regular monitoring data can inform investment decisions all on their own. We came across a government agency that used the web to provide services to its citizens. Its costs for adding new features to its web application were being significantly increased by the cost to support older browsers - which was considered mandatory for those citizens that couldn't upgrade. Looking at the traffic revealed that so few citizens used such older browsers that rather than supporting the old browser, it would be cheaper to give them a new computer and a bunch of flowers.

If you're moving to the cloud, take just the valuable bits

With this rise of cloud systems, we are seeing many organizations wishing to move their software systems to cloud hosting. This parallels a long history of system replacements, where companies look to replace existing systems with something that supports the same capabilities but runs on more modern (and hopefully more efficient) infrastructure. With several decades of seeing these kinds of efforts during our careers, we've seen that there are easy mistakes to make. Perhaps the most common of these is the idea that the simplest way to do a system replacement is a feature-parity replacement that seeks to exactly mimic the existing functionality on a new platform. Such a like-for-like approach misses the fact that much existing functionality is of little value, some not used at all, and some actively interfering with an optimal business process. A feature-parity replacement is harder than people usually think, and taking the time to avoid copying little-used functions pays for itself easily.

One organisation we worked with kicked off a migration effort by moving 100% of their logistics handling code into a new system, this took several months and involved many of their development staff. When we talked to the business about their future plans they explained they planned to drop support for many kinds of packaging due to high costs. Dealing with all the edge cases around the packaging turned out to be the thing that consumed most time on the migration, and yet the business would have been happy without it.

Understanding the contribution to business value can thus be a significant help in identifying how to do a better re-platforming effort. If existing components aren't contributing much value, then they shouldn't be copied into the new platform. A common case here is a service company that has most of its services follow a few common cases, but has a few unusual offerings that only come up rarely. Such unusual cases often involve special software support - but such marginal cases should always be reviewed before they are re-implemented on a new platform. If the business expects to stop oferring this service in the next six months, that's something that should be understood as part of the re-implementation plan.

Business value is vital but inconstant

As with anything in life or software architecture, such assessments of value aren't constant. We worked with an insurance company that had a competitive advantage through its rating model. This software was seen as one of the company's crown jewels. But over time there was a big shift to doing insurance quotes on-line with straight-through processing. The crown jewel required lots of parameters, which could reasonably be captured in the pre-online era with an agent meeting with the customer, but the complicated form was too unappealing on the web. With this shift the value of their crown jewel withered away. So as well as getting an understanding of the current value of software assets, it's worth trying do a rough forecast of how that value is affected by changes in the technical and business environment.

Another case was retailer whose catalog management system coped comfortably with updating twice a year, but couldn't deal with the shift to rapid online changes. The opportunity cost of lost revenue is never an easy thing to quantify, but it needs to be considered when deciding where to place an investment in restructuring or rewriting components.

Business knowledge should be part of a technical career path

When people look at the growth of technical leaders, most attention tends to go into “hard” technical subjects. Training courses (certified, no less) abound for various software platforms. For technical skills development we advocate training that focuses on core principles rather than today’s popular platform. Wise skill development realizes that the much more difficult area of “soft” skills (note our irony-quotes) become increasingly important as folks rise up the leadership ladder, and that's something we endorse too. [1]

Valuable though these things are, we also think it's vital to ensure technical leaders have a firm understanding of the business they operate in, and how value is generated by the various players in the domain. This is usually not something that comes through training courses, rather it's something that comes through regular interaction with business leaders. This social interaction should begin early in a technologist's career. The notion that separating IT staff from business staff causes untold ills to such a profession like software development whose value is rooted in how much software is deeply entwined in the activity of the enterprise it supports. Developers need to learn early on that constant contact with their users and customer is normal, and learn how to do it well. Years of such contact reap great rewards when they become leaders and are familiar with those in the business that they have grown up with.

The barriers in communication between business and IT has been one of the sadly enduring themes of our long careers in software development. When architects are disconnected from the understanding the flow of business value, it raises costs both in wasted technical effort and in loss of opportunities presented by changes in the environment. Software leaders need to put more attention into the interplay of business activities and software decision making, and ensure that this is part of the career development process for all the technical staff.


1: These are called “soft” skills because they are harder than “hard” skills.


This article germinated when Martin, wondering what to say when invited to give a keynote at O'Reilly's Software Architecture Conference, asked his colleagues for ideas at dinner after a ThoughtWorks Technology Radar meeting. There was a general consensus that too many architects were not aware enough of business value, and Ian was particularly forceful in expressing their concern. Ian and Martin then collaborated on writing this article (and Martin did his talk).

Andy Birds, Dave Elliman, Eduardo Aquiles, Erik Dörnenburg, Jeff Mangan, Kevin Yeung, Peter Gillard-Moss, Rebecca Parsons, Scott Shaw, Sharath Satish, and Wojciech Milewski discussed drafts of this article on our internal mailing lists. These discussions provided many of the examples we use in the article.

The talk is available on O'Reilly's platform, but behind their paywall.

Significant Revisions

02 March 2020: published