Effective business processes foster collaboration, data traceability, and outcome consistency. They structure the activities and interdependencies that maximise quality, minimise cross-functional delivery time, and keep individual contributors moving forward.
They must be aligned to data, teams, and organisational maturity. Lack of definition leads to sub-optimum operations and a perceived loss of control; too-constraining processes hinder creativity and experimentation.
There's typically no one-size-fits-all approach to business process design, re-engineering, or operational optimisation. Process design means structuring information and data, activities, events, roles, interactions, and decisions — continuously balancing across six perspectives:
- 1. Organisational — How the business operates — start-up or established, and at what operational maturity.
- 2. Data — What type of information, the data lifecycle, functional flows, data volumes, structural complexity, quality acceptance criteria, control level, and so on.
- 3. Collaborative — How teams communicate and exchange data, and which decisions they make from it — and when.
- 4. Outsourcing — How the organisation works with suppliers and customers, and how it capitalises on the collective knowledge base.
- 5. Governance — How cross-functional teams track progress, manage issues, risks, changes, approvals, and decisions.
- 6. Tool and IT platform — How data is stored, controlled, accessed, integrated — and how out-of-the-box processes are implemented and configured against the best practices embedded in the chosen systems.
Several process mapping and analysis techniques sit on top of those foundations: data-flow diagrams, decision analysis, data modelling, business-rules analysis, KPIs, process modelling, problem tracking, organisational modelling, use-case definition, system and functional assessment. This article covers the value of effective process design and mapping, and the QR_ approach to value-driven process solutioning and problem solving.
Business process design: where to start
Business process mapping is core to business analysis and continuous improvement. As the International Institute of Business Analysis defines it in the Business Analysis Body of Knowledge: a business process represents "a set of defined ad-hoc or sequenced collaborative activities performed in a repeatable fashion by an organisation. Processes are triggered by events and may have multiple possible outcomes. A successful outcome of a process will deliver value to one or more stakeholders" (IIBA, 2005).
Product development operations require a combination of formal and informal practices across communication, collaboration, learning, people, and data management — tailored throughout the product lifecycle and calibrated to organisational maturity. The reality on most engineering processes: around 80% of what you need can be implemented from experience combined with out-of-the-box platforms and industry best practice. The remaining 20% typically requires bespoke configuration to the specific business context.
Value from business process re-engineering
Originally developed by the Business Process Management Initiative, business process modelling notation (BPMN) helps with graphical process representation and technical documentation based on internationally recognised standards. It brings consistency to process analysis, definition, improvement, and re-engineering.
Process maturity is a relative measure that links to a capability maturity model (CMM), aiming to address considerations such as:
- Is the process fit-for-purpose to support the relevant delivery operations, without hindering needed flexibility?
- How is the process helping teams and individuals make timely decisions — in business benefit terms?
- How and when is the work completed and documented?
- What's the level of integration across functions, and how are teams empowered?
- Is the process effective (well-defined, meeting business objectives) and efficient (seamless in execution, repeatable)?
Existing process improvement drives bottom-up adjustments, extensions, and issue resolution. Continuous improvement is core to any operation and part of the learning organisation — but it relies on progressive changes and limited disruption.
Process re-engineering drives more top-down opportunity for improvement, with the potential to significantly transform how a company operates. It needs organisational change management, user education, and/or job-design alignment to land properly.
Either way, business process analysis covers AS IS process and pain-point mapping, fit-gap analysis, value-stream mapping, and improvement-opportunity identification. That pairs with TO BE process definition, keeping the big picture in view and driving transition and deployment strategies. Digital tools, enterprise platforms, integrations, and automations are the enablers — covering access security, role-based interactions, advanced search, reconciled business analytics.
Combining process implementation and execution
Processes are defined for a given purpose and context. New processes are typically designed following a right-to-left approach, working backwards from the new-product-development delivery milestone. That's most relevant for start-ups, new business units, or business transformation roadmaps. An iterative approach is essential — so the learning feeds back into the transformation — with a focus on right-sized solutions. It's also sometimes necessary to cut short the process debate and focus on time-to-value through quick-win implementations. Organisations benefit from punctual decisions and the operating velocity that follows from them.
QR_ makes a difference on product development process engineering by combining a tailored, holistic approach across both process implementation and execution:
- Process implementation — Strong focus on interdependencies and maturity — building a high-level view of when data needs to be available, and how it moves from one business function to another.
- Process execution — Running the operations — as a key user group, or in a support capacity to the business — understanding which decisions will be made from the process and its associated data, and empowering downstream activities to reinforce collaboration.
As organisations scale and mature, clear process ownership becomes critical — from champions to data stewards, acting as gatekeepers of the process and the data it governs. Business analytics then feed back into measuring and improving both how processes are implemented and how they run. Essential knowledge gets gathered from multiple perspectives and experiences to define effective implementation roadmaps. Whatever the context, strong stakeholder management throughout — and a critical eye on the bigger picture — are non-negotiable.
What are your thoughts?
Thanks to Luyao Zheng, consultant at QR_, for her valuable contribution to this discussion. https://linkedin.com/in/luyaozheng/
References
IIBA, International Institute of Business Analysis (2005); A Guide to the Business Analysis Body of Knowledge (BABoK v2.0).
