Factors of Organisational and Digital Transformation

Organisation

  • Line of business
  • Risk register / immediate risks
  • Risk appetite
  • Public / private / shareholding / equity holding
  • Impediments and current challenge
  • Tracking up or tracking down
  • Industry volatility and disruption
  • Competitors
  • Urgency
  • Cost of delays
  • Cost of changes
  • Regulatory compliance needs
  • Locations
  • Time zones
  • Organisation size
  • Organisation age
  • Diversity of business lines/units
  • Purpose and values
  • Mission statement
  • History and folklore
  • Past mergers and acquisitions
  • Organisation identity in the world
  • Public or private
  • Short term pressure / long term pressure
  • Heterogeneity of leadership / board
  • Finances – cash, P&L, share price, turnover, EBITDA
  • Cost sensitivity
  • Preference for opex vs capex
  • Exit strategy

 

People

  • Organisational culture
  • Heterogeneity of culture across the organisation
  • Leadership buy-in to transformation
  • Key stakeholders
  • Prior transformation attempts
  • Psychological safety (org-wide / in-team)
  • Customer expectations
  • Customer base (business, consumer, public, other)
  • Ease of customer feedback
  • Diversity
  • Equality, gender pay gap visibility
  • National identity and culture
  • Survival anxiety
  • Team member churn rate / length of tenure
  • Organisational structure, reporting lines, matrix, hierarchies
  • Geographical distribution
  • Permanent teams vs outsourced teams
  • Skill and mastery level
  • Tacit knowledge in the organisation
  • Capabilities and gaps
  • Promotions, recognitions and awards
  • Pay scales
  • Orthodoxies
  • Defined roles
  • Cross-teaming
  • Training, coaching, mentoring, support
  • Career paths
  • Physical working environment
  • Communities of Practice
  • Remote vs on-prem (degrees of remoteness)
  • Longevity of teams
  • Centres of Excellence / Enablement
  • Stream aligned teams / function-aligned teams / hybrid
  • Known rituals
  • Facilities, office design, open vs closed offices, physical space
  • Exposure to “business” information such as cashflow, profit, turnover, and granularity.

 

 

Process

  • Operating model
  • Policies
  • Standards
  • Processes
  • Regulation of process
  • Standardisation appetite
  • Finance process
  • Budget cycle
  • Business case requirement
  • Hiring process
  • Procurement process and duration
  • Adherence to frameworks
  • International & national standards
  • Audit frequency and type
  • Governance, risk, compliance processes
  • Product vs project
  • ITIL / COBIT / other frameworks
  • Environment provisioning
  • Preference for waterfall vs agile
  • Handoffs
  • WIP limits
  • Communications cadences and expectations
  • Current methodologies and practices
  • Security clearances
  • Natural / habitual cadences
  • Agile adoption
  • Scrum adoption
  • Methodologies at scale (SAFe, LESS, etc)
  • Statistical Process Control – level of automation and adoption

 

Data and Tools

  • Wall space or digital tools – information radiators
  • Data-driven insights capability
  • Communication tools – asynchronous vs synchronous
  • Silos of information
  • Data feedback loops
  • Dataviz and analytic tools
  • Degree of tool integration
  • SSO
  • “Shadow” IT
  • Degree of autonomy / lockdown of machines
  • AI/ML
  • Volume of data
  • Information availability, default to open/closed
  • Data treated as asset or liability
  • Default information openness
  • Dashboarding and reporting

 

Products

  • Number and characteristics of key products
  • Criticality (life/death or just for fun)
  • Cost of delay for features
  • Level of planning expectation
  • Estimates and deadlines required
  • Risk appetite
  • Reliability requirements
  • Scaling requirements
  • Quality requirements
  • Degree of coupling
  • Degree of cohesion
  • Current lead time
  • Current flow / wait time
  • Current quality
  • Internal regulation
  • Unplanned vs planned work
  • Product lifespan
  • Feature lifespan
  • Marketing approach and capabilities

 

Technology

  • Satisfaction of technical capability
  • Common platform?
  • Architecture – monolithic vs microservices / APIs
  • Potential fracture planes
  • Team topology
  • Corporate network (MPLS, VPNs, hybrid, SDN, etc)
  • Cloud usage (production) – private/hybrid/public
  • Edge and IoT technology
  • Preferred technologies and codebase
  • Build and Deployment pipelines
  • Deployment strategies – canary, blue/green, rolling, A/B
  • Engineering skills
  • Engineering practices
  • Service Desk?
  • Infra as code
  • Containerisation
  • Test and QA approach
  • Work definition approach – user stories, MoSCoW etc
  • Rate, predictability and volume of work requests
  • Where does work come from?
  • Environments
  • Monitoring and observability
  • Degree of automation
  • Branching strategies
  • Existing reliability
  • Existing rate of change
  • Accelerate metrics
  • Technical debt
  • Pair programming, mob programming practices
  • Ratio of junior to senior engineers
  • Dev workstations and tooling
  • Dev / Ops teams & handovers
  • On-call culture and process
  • Infosec team / function and interactions

Please feel free to use this however you’d like, and if you think something needs adding to this list of organisational transformation factors, please let me know!

Digital Transformation and DevOps: Enterprise Resilience

digital transformation

Digital Transformation is having a real moment in industry, in part due to the huge changes as a result of the pandemic of 2020.  But as usual, there’s little agreement about what it means. In contrast to previous “transformations” such as ITIL, Lean, Agile, or DevOps, digital transformation doesn’t simply mean automating processes, becoming more efficient, offering your existing products and services online, creating an app, or shifting your infrastructure to the cloud. Even the annual State of DevOps Reports are beginning to focus more on digital and organisational transformation rather than a specific focus solely on DevOps.

What is digital transformation?

True digital transformation means transforming everything about your organisation in respect to people and technology towards an engaged, agile, happy and high performing organisation. DevOps was (and still is) one key aspect of this approach. The only way to truly achieve organisational resilience or enterprise agility is to fundamentally transform the foundations of the organisation. The list below describes just some of the aspects of digital transformation and the areas to address

  • Culture, values and behaviours
  • Practices and ways of working
  • Communication structures
  • Hierarchies
  • How financial budgets and funding models are managed
  • How teams and people are measured and incentivised
  • How and what metrics are used
  • Cloud native architectures and practices
  • Moving from projects to products
  • Team structures, topologies and interactions
  • Recruitment and onboarding/offboarding practices
  • Value stream alignment
  • Breaking down silos
  • Embedding the ability to change and adapt
  • Reducing cognitive load
  • Psychological safety in delivery teams, senior leadership teams and functional teams
  • IT services and operational technologies
  • Facilities, colocation, office layouts (especially options for open-plan or not)
  • And many many more – in fact, here is an (incomplete) list of organisational factors relevant to transformation.

Why digital transformation?

What’s your organisational goal? Maybe it’s increasing your speed to market for new products and features, maybe it’s reducing risk of failure in production and improving reliability, or maybe it’s to keep doing what you’re doing but with less stress and improved flow. If you’re only looking to reduce costs however, digital transformation is not for you: one of the core requirements for a transformation to succeed is for everyone in the organisation to be psychologically safe, engaged and get behind it, so reducing costs and potentially cutting workforce numbers is not going to create that movement.

What is Enterprise Resilience?

Resilience Engineering is a decades-old field of applied research that focusses on the capacity to anticipate, detect, respond to and adapt to change. Organisational “robustness” might mean being able to withstand massive disrupting events such as pandemics or competition, but enterprise agility represents the resilience engineering concept of true resilience – not just “coping” with change, but improving from it and future challenges. I believe that Resilience Engineering is the direction that DevOps is evolving into.

Why is digital transformation so complex?

Despite many attempts to simplify the concept of digital transformation, it remains one of the most challenging endeavours we could embark upon.

Galbraith Star model
Galbraith Star model

I’m not a huge fan of over-simplifying organisational complexity into components, especially models such as Galbraith’s Star that place “people” as one of the components (and certainly not models that consider anything other than people to be the primary element). Whilst models such as this may help people compartmentalise the transformation challenge, in almost every case, the fractures between the various components don’t actually exist in the way they’re presented.

Organisations are not simply jigsaw pieces of technology, tools, and people that react and function in predictable ways. As the Cynefin model shows us, complex systems, such as sociotechnical systems (the organisations that we work in) require a probe-sense-respond approach that has built-in feedback loops to determine what effect the intervention you’re working on is having. Everything in digital transformation is an experiment.

upload.wikimedia.org/wikipedia/commons/1/15/Cyn...

It’s also important to avoid localised optimisation – applying digital transformation approaches to one part of an organisation whilst ignoring other parts will only result in tension, bottlenecks, high-friction and failures elsewhere. Likewise, changing one small part of a system, especially a complex system, will have unintended and unanticipated effects elsewhere, so a complete, holistic view of the entire organisation is critical.

Digital transformation is a series of experiments

This is why, if anyone suggests that there is a detailed “roadmap”, or even worse, a Gannt chart, for a digital transformation project, at best it’s naive and worst, it’s fiction. Any digital transformation process must be made not of a fixed plan, but a series of experiments that allow for iterative improvements to be made.

Digital transformaiton - everything is an experiment

When you think about digital transformation in this way, it also becomes clear why it will never be “finished”. Organisations, like the people they consist of, constantly change and evolve, just like the world we operate in, so whilst digital transformation is undoubtedly of huge value and an effective approach to organisational change, you will never, ever, be “done”.

In my role as Transformation Lead at Red Hat Open Innovation Labs, we use the Mobius Loop approach to provide structure to this experimental, feedback-based, continuous improvement and transformation journey.  If you’re interested in digital transformation, DevOps, Psychological Safety and how you can begin to set transformation in motion in your own organisation, get in touch.