Value Stream Operating Model Transformation – Ten Leadership Essentials

Soaring Customer Expectations that…

“The last outstanding experience customers have becomes the minimum expectation for their next experience”.

The ratcheting up of customer expectations is not limited to traditional retailers. A superlative retail experience sets consumer expectations for all industries, and for every stakeholder, customers, employees, and ecosystem partners. Today, customers expect to conduct all business digitally, wherever, and whenever, using any device, with all the supporting information and content they need close at hand.

This shift in expectations is both threat and opportunity: an opportunity to gain market share by meeting expectations, or to fall behind if such expectations are not met.

…Drive Digital Transformation, requiring…

As customers demand more, emerging technologies are offering new ways of meeting those needs. Digital transformation is a way of leveraging new technologies such as cloud, AI, and analytics.

Done well, digital transformation embraces every business function, including: 

• Reinventing business models (e-commerce, electronic delivery).
• Optimizing processes (supply chain management, new feature development).
• Enhancing customer experience (in-context customer reviews, personalized recommendations).

In parallel, as digital transformation reshapes business, operating model transformation is the hidden nine tenths of the iceberg that accelerates the pulse rate of the organization to deliver experiences and realize high value outcomes. Over the past decade, there has been a surge in operating model re-orientation towards product-oriented models to support these digital transformations. But we are beginning to see the limitations of these operating models, as organizations struggle to deliver value that cuts across a complex organizational and technology landscape. In recent years we are seeing an alternative model emerge, orienting operating models around value streams, that is showing promise.

…Value Stream Operating Model Transformations – 10 Essentials

A value stream is itself not a new concept.  It is used in the scaled agile framework and is defined as “a series of steps that an organization uses to implement Solutions that provide a continuous flow of value to a customer”. What is new to many organizations is how to think about orienting their teams and operations around their most important, highest impact value streams. We are actively working with many institutions on value stream transformations and have observed a common set of challenges with resolutions, which we characterize as “10 Essentials” to getting to a value stream oriented operating model:

Figure 1: Summary of Resolutions for Activating a Value Stream Operating Model

Challenge 1: Conceptual Strategy

Often clients do not translate a business strategy into personas/customer journeys, and value potential. Without such translation, the delivery work does not always lead to clear and measurable value. This can cause frustration amongst senior business executives, diminishing support for the program.

Resolution: Straight through strategy to value

It is vital to have a clear line of sight from strategy to personas/journeys and value. Without that, teams can lose sight of outcomes and lose time on low impact work: the value needs to drive the work. 

Figure 2 illustrates how a cargo division of a large global airline shaped a value tree for the Enterprise Sales value stream, defined a set of personas and their journeys, and tied the journeys explicitly to the value drivers within the value tree. They discovered that out of more than a dozen personas, three of the personas drove 80% of the value. This brought powerful clarity and focus to the development team

Figure 2: Value Orchestration Methodology Example 

Challenge 2: Business Execution Resistance

Transformation programs are often sponsored by CIOs, and even though the business executives nod at the program, they are not ready and willing to give the support, resources, and investment needed to transition to the new operating model. For example, if value stream work cuts across multiple lines of business, business leaders may not be willing to change their processes to support the value stream given their incentives to go after line of business specific initiatives. Establishing a product management function will help solve the design and execution of the technology work, but it will not solve the problem around changing the way business works.

Resolution: Senior business executive commitment with operations re-alignment

Getting the business to make the changes needed to realize the of a product management model can be challenging. There are several fundamental approaches to re-align operations:

• Move the new business processes into a shadow organization and run the new value streams in parallel to existing business processes.
• Re-align existing teams to value streams out of the gates and build capabilities into these team to incentivize and enable them to operate differently
• Run "virtual" value stream teams, where teams from different business units are matrixed into the value streams and appropriate incentives are established to ensure the virtual teams missions are aligned with the business units

For any of these to work, two things need to be in place: 1) a “two-in-a-box” approach where both the business and IT leaders are jointly responsible for shaping and executing on a value stream operating model transformation, 2) CEO/COO participation and oversight of the program to drive alignment across teams. 

For example, a large North American credit union had recently embarked on a broad scale operating model and digital transformation. The CEO was the primary sponsor of the initiative, where he publicly announced the plan to fully transform the business, along with substantial value aspirations. He gave concrete targets to his business reports and ensured his business leaders were joined at the hip with IT. Two years into the transformation the organization had largely completed the operating model transition and delivered more than $500M in value.

Challenge 3: Capability Mismatch

As companies transition to a new style of delivery, teams need to learn new ways of working (e.g., product management, agile/DevOps delivery, value-based design thinking). Many companies attempt to teach their teams these new skills by developing an on-line curriculum. This is often insufficient to make the transition for two reasons: 1) the self-service learning model only works when staff are hungry for such learning, 2) staff often fail to make the behavioral changes required to implement what they have learned “in class.” As a result, teams don’t learn the full breadth of skills needed to transition to new operating model or fall back on old ways of working.

Resolution: Operationalize Adult Learning

We find that leveraging the full breadth of adult learning levers is required to transition teams to this new mindset:

1. Learn by observation (e.g., class room, on-line learning)
2. Learn by doing (e.g., Bootcamps, Dojos)
3. Learn by sharing/coaching (e.g., Centers of Competencies, Brown Bag Discussions, Code Reviews)

For example, a large global bank recently underwent a large scale agile and DevOps transformation. To build these new skills and mindsets within their teams, they established a “Dojo” capability building module, in addition to an on-line learning curriculum, where they deployed agile and DevOps coaches into teams and in a highly structured set of ceremonies, taught their teams new ways of working while solving real world problems. In addition, they stood up knowledge/code sharing sites and ran “brown-bag” sessions to encourage their teams to teach one-another.

Challenge 4: Culture Mismatch

While persistent teams in value streams are more productive than fluid teams, they work much better if team members are willing to branch out and learn a broader set of skills outside their area of expertise. However, many IT shops are dominated by “expert” driven mindsets, which can get in the way of learning and limit productivity.

Resolution: Legitimize experimentation and failure if used for learning and course correction

Fail fast is a mantra often heard with agile teams. However, the goal is learning, not failure. Our experience shows that benefiting from a culture of experimentation requires a dual approach: 1) Creating an environment where people and teams are comfortable taking a chance that might not succeed, 2) Having practices that review current practices and outcomes and constructively work through solutions to improve. In other words, failure without learning is costly, and learning is the key to creating value from failure. This requires a change in three leadership behaviors:

1. Employing agile and design thinking practices
2. Adopting a fact-based (or data-driven) approach to know what is successful and what needs to be improved
3. Creating a climate of psychological safety where prudent risk-taking is encouraged, but critically, insisting on learning practices that ensure failures do not repeat

Though most people agree in principle that a learning mindset and culture is critical to driving growth and continuous improvement, too few adopt the behaviors to establish a learning mindset and culture. There are a well understood set of levers and leadership behaviors that can be leveraged to creating a learning culture.

For example, one of the world’s largest investment banks made this shift. At the outset, leaders did the opposite – failure was treated extremely harshly, so executives were gun shy about experimentation, and (worse) when failure did happen, the focus was on reprisals and not learning. By focusing on specific behaviors, we were able to “invert” these practices.

Challenge 5: Architectural Coupling

Systems and applications tend to be aligned along functions (e.g., claims), but are rarely aligned against end-to-end value streams. This leads to value stream teams being coupled to one-another as they depend on a common set of applications and systems. This slows down delivery by placing a high coordination burden on teams. However, aligning systems completely to value streams can create technology “bloat”, as systems can be duplicated across the value streams. This creates a trade-off between business enablement and IT efficiency and many IT organizations struggle with getting the balance right.

Resolution: Remove Architecture Barriers

To help teams operate autonomously, it is important they can make technology decisions relatively independently from other teams. However, it is rarely possible to eliminate cross-team technology dependencies, particularly in environments with a lot of legacy. 

There are a few technology architecture and design patterns that can help alleviate the dependencies across teams. One popular way to reduce the burden of managing technology dependencies is to establish an event driven and API based decoupling layer, along with proper architectural oversight to enforce RESTFUL APIs and forward/backward compatible messaging. 

For example, a large North American insurance company recently embarked on a large-scale digital transformation. However, before launching specific digital initiatives, they spent 3-6 months standing up a digital mesh and establishing a set of standards around this mesh. Though this delayed the launch of digital initiatives upfront, once this platform was established the value stream teams were able to operate independently from the other teams. As a result, they were able to operate in much more rapid release cycles.

Challenge 6: Data Swamps

Even if enterprises can stand up a proper decoupling architecture, data format inconsistencies, difficulty in finding and understanding required data, and poor data quality can lead to execution challenges down-stream and can slow down the pace of delivery. In the worst-case scenarios, these programs can get overwhelmed with data problems, leading to program delivery issues downstream.

Resolution: Get Control of the Data

Many leading companies favor a Center of Excellence for incubate their data expertise . The right design of such Centers balances both control and autonomy. Federated data management models are rapidly becoming the norm, with the use of data fabrics (and the associated technologies) as relatively light-weight ways to manage consistency of data across the federation.  

For example, a large global automobile manufacturing company recently began a large-scale transformation of their inquiry to delivery value stream, which promises to deliver nearly $1B in EBITDA. This team established a centralized data management function to provide data curation, lineage management, and meta data management of the data sources aligned to various logistics teams. This in turn enabled them to drive much broader and more reliable visibility and insight into the end-to-end logistics process.

Challenge 7: Cumbersome Governance

Most programs put in place agile governance mechanisms to manage value streams more like products than projects. However, leaders often struggle to transition to a more agile mindset, forcing teams to develop cumbersome business cases before approving release cycles, which recreates traditional project-based governance. This slows down project delivery and does not give teams the breathing room to learn and adapt. Most companies are shifting to a DevOps model to improve both the quality and speed for delivery of new capabilities.

Resolution: Top Down, vs Bottom Up, Governance

Leading companies create a stage gate process to value stream governance. However, for these processes to work best, decisions on how dollars are spent needs to be pushed down to the product teams. Governance really needs to be focused on high level allocation of dollars based on strategic imperatives, vs. a summation of project ROIs. In addition, there needs to be discipline and agility around moving resources. One litmus test of effective governance is how many initiatives are stopped, and how quickly those resources are redeployed.

Challenge 8: Brittle Managed Service Agreements

Modern companies are a complex network of internal and external capabilities. The challenge is that the partnership agreements supporting legacy environments are often structured to be predictable, not agile, so running an agile style delivery model within these contracts is very difficult. In addition, there may be knowledge asymmetry, where most of the critical knowledge sits within the vendors and not the enterprise, which makes it challenging to shape and drive change across the ecosystem

Resolution: Consider the whole ecosystem

To achieve broader agility and DevOps integration, your talent management and ecosystem need to be on the same journey. Vendors and suppliers need to adapt their models, contracts, and measurements to allow for new team dynamics, ways of working, and speed of the agile teams. 

For example, a large global automobile rental company recently began a large-scale digital transformation. The challenge they faced is that nearly 90% of their application portfolio was outsourced to a third-party provider, and that the managed services agreement was a traditional, highly SLA oriented structure that made it difficult for this company to apply modern DevOps style delivery techniques. To overcome this problem, this company pulled in critical resources (e.g., product management, architecture) and restructured the agreement to enable PODs to be formed with joint vendor and enterprise objectives.

Challenge 9: Big Bang Execution

Programs that don’t demonstrate value quickly and often run the risk of “change fatigue “and senior business executives getting frustrated. “No battle plan survives first contact with the enemy” and launching at scale denies the business the chance to learn from pilots and adds substantial risk to the program.

Resolution: Start small and scale responsibly

Three things are critical at the pilot stage. The first is that the program shows wins early and continuously, otherwise senior executives can grow cynical, and the program can lose momentum. Secondly, such successes must be properly communicated; project reversals attract a lot of attention, and it is the job of change management to make sure successes receive their due attention as well. Thirdly, take a measured approach to scaling, that is start with a pilot, drive pilot learning through the business, then scale out to remaining value streams in phases.

Challenge 10: Slow Delivery

Even though many enterprises have adapted Agile delivery practices, many processes along the application delivery value chain remain highly manual. This can both limit the impact of agile adoption, as well increase the rate at which errors are introduced into production as teams attempt to accelerate cycle times

Resolution: Get to DevOps

One solution is to create a DevOps Center of Excellence to drive adoption of DevOps. However, for DevOps to operate effectively, both development and operations teams need to operate as one, with many of the application maintenance functions to be embedded within the value streams.

In conclusion…

Value stream operating model transformations are complex, but with the right guidance and attention to these 10 essentials, your leadership can avoid some of the pitfalls that slow delivery and reduce operational excellence.