Value stream mapping: zooming on business change and building continuous improvement strategies

Business value drives decisions — and, downstream of that, improvement and change requirements. Value mapping covers the full value chain, from suppliers through to customers and end-users, with the big picture held in view so teams can identify and prioritise the right opportunities for improvement.

In lean terms, value stream mapping is the glue between data flow and the decision-making process. It's not about telling people what to do when, and it's not about efficiency in the "make people work faster or harder" sense. Its purpose is to empower stakeholders at every level to plan how and when to implement changes that add real value — and ultimately meet or exceed customer expectations.

It helps business leads, process owners, and management teams understand problem statements and place them in wider business context. In parallel, it helps data stewards and key users get inside data and process interdependencies, and work out where the improvement opportunities actually are.

The idea behind value-stream analysis is to look beyond individual processes and individual roles, and focus instead on upstream and downstream data flows and the processes they feed. Done well, the analysis usually extends past data and business processes into considerations like skills, knowledge, team and organisational structure, training, onboarding, operations, governance, and business analytics. This article covers how value streams can be interpreted to develop business cases and drive transformation roadmaps.

It means alternating between multiple lenses — wider angle, fixed focal length, or zoom — to understand different perspectives across the business and deep-dive where necessary.

Beyond process continuous improvement

Value stream mapping (VSM) was introduced in the late 1990s by Rother and Shook as a way of "seeing" — visualising — business value across multiple perspectives: processes, teams, personas, organisations, data sets, systems, interfaces. It started as a manufacturing production-waste identification tool (process kaizen), but the approach carries all the way up from the shopfloor to the management top-floor.

Value-stream improvement can also help build better product development operations, even if the link between business metrics and decision-making is less tangible there than it is in production execution.

Rother and Shook talk about "learning to see" and describe future-state VSM as a visual "blueprint for lean transformations" in continuous improvement terms. Simply put, VSM is a way to frame contextual problem statements, brainstorm opportunities for improvement, and build the business case to justify the work.

VSM is a current-state versus future-state fit-gap analysis. Future-state ideas come from industry lessons learned and enterprise-platform best practice (externally benchmarked), or from new solution opportunities found within the organisation (internal creativity). Most often it's some combination of the two. It's also shaped by organisational maturity, cultural factors, and the business's ability to absorb change — small or large. VSM is contextual to a set of stakeholders, and is typically performed as part of a broader enterprise architecture initiative.

Start-ups and new product development projects may not have a current state to map — instead, they consciously seek to do things differently by building on creative opportunities and partnerships with subject-matter experts. That takes a combination of inside-out and outside-in learning and leadership. Inside-out and outside-in value assessments bring new perspectives to the table while accounting for how teams currently work.

Defining core business value statements

Value statements set out the expected business benefits — even if aspirational or yet-to-be-validated — with top- or bottom-line results that can be measured across multiple personas. Each persona represents a high-level business function or role, and each role drives its own perspectives and expectations.

As Nash and Poling (2008) point out, it's often wrongly assumed that value statements are highly speculative or subjective — not data-driven — relying on stakeholder opinion. VSM actually does the opposite: it shows where data comes into play, how it's collected and shared, and which decisions are based on it (operational data analytics). Business value is typically derived from a balanced combination of improvement steps and enabling-capability introduction (or re-implementation).

Nash and Poling also argue that VSM techniques are easier to apply to product or transactional processes. They describe process mapping as "a stream of activities that transforms a well-defined input or set of inputs into a predefined set of outputs." Business benefits are what drives implementation prioritisation against an enterprise improvement backlog.

A practical principle: under-estimate benefits to set realistic expectations, while aiming to over-deliver and keeping any foreseen risk mitigation within budget, time, and quality expectations. Expected ROI should stay conservative — while still being attractive enough for top management to commit to the transformation, and for the work to have robust boundary conditions guiding concerted process re-engineering.

Some organisations prefer to define a utopian "change vision" to inspire the workforce, hoping the implementation roadmap will eventually steer the business in the right direction. That doesn't align well with VSM philosophy or practice. The change vision needs SMART, achievable objectives — otherwise unrealistic promises erode trust and mobilisation over time, producing the opposite of the intended effect.

Building business change roadmaps

VSM combines methodologies and techniques to start down the path to continuous change and improvement. It's an ongoing journey, not a one-off study. Most agile frameworks refer to value streams as a phased way to deliver a "continuous flow of value to a customer" — what Scaled Agile calls customer-centricity.

VSM is an effective way to gather business requirements when implementing, configuring, or improving enterprise digital platforms (PLM, ERP, MES). When it comes to value identification and realisation, data analytics are both input and output — used to quantify value opportunities and compare improvement outcomes. A non-exhaustive set of questions worth putting to stakeholders:

• Which data is most relevant across personas and stakeholder perspectives?
• What are the relevant data sources, and how do they connect?
• What data is essential for which decisions?
• Is there sufficient data to quantify process effectiveness and efficiency?
• How do we make sense of the core data, and separate it from the noise?
• Is there industry benchmark data to fill the gaps where internal metrics don't exist?
• How do we address start-ups, where there isn't much data to look at in the first instance?

These questions — and many others — are essential discussion topics with business stakeholders when mapping information flows, systems and process landscapes, and value drivers. It's also important to avoid pushing a single VSM methodology onto an organisation, and instead adapt the approach to context, leveraging both internal and external perspectives. Being able to concurrently define, run, improve, and re-engineer business processes and operational governance — while ensuring business continuity — is a genuinely rare skillset.

What are your thoughts?

Thanks to Romit Samani, Business Leader at QR_, for his valuable input to this discussion. https://www.linkedin.com/in/romit-samani-015058b3/

References

Grealou L (2016); Value is in the Eye of the Beholder; virtual+digital.

Nash MA, Poling SR (2008); Mapping the Total Value Stream: A Comprehensive Guide for Production and Transactional Processes; CRC Press.

Rother M, Shook J (1999); Learning to See: Value Stream Mapping to Create Value and Eliminate Muda; Lean Enterprise Institute.