Methodshift

3 Steps Towards Data-Driven Delivery
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The 3 Essential Steps to Transform Your Organisation’s Agile Delivery with Data

At Methodshift, we work closely with organisations helping them to transform their software delivery ecosystems to be more automated, transparent, and data-informed. Their primary goal is often to build transparency, improve performance and reduce costs in these tricky economic times. We help them achieve this by generating delivery & performance insights, and consolidating their fragmented and expensive tooling with our Mission Control software delivery platform.

We’ve identified three steps organisations must make to reap the full benefits of increased transparency and data insight. Each stage presents its own challenges and obstacles.

Here are the 3 steps we’ve identified:

Step 1: Agile Foundations at Team Level

Before you can fully empower your organisation with data, you need to lay the foundations. The vast majority of organisations operating at scale struggle to build a clear, up-to-date, and automated picture of each team’s performance and delivery.

Out-of-the-box project management software like Jira does not provide the tools to support this. It is too generic and flexible, often resulting in a chaotic mess. This is one of the reasons that Jira gets a lot of criticism.

In large-scale organisations, the struggle to view a teams roadmap, or understand when an item of work is expected to be delivered is real. These artefacts are often scattered or hidden in the deep recesses of Jira, Miro, Confluence, or worse… an Excel sheet.

An example of a manual roadmap created in confluence

 

To compound things, each team operates differently—some prefer kanban, others use scrum, and some rely on story points or ticket counts with probabilistic forecasting. Project management tools such as Jira fail to accommodate these varied agile approaches and techniques, leading to a fragmented picture.

The transformation at this step requires making team operations immediately inspectable to promote feedback loops and supporting them with relevant data insights. In addition promoting agile, delivery, and Jira best practices without compromising teams autonomy.

Most tools expect rigid conformity to provide insights. You are either kanban, or scrum, you story point or you dont. Our platform, Mission Control, addresses this by being intelligent and adaptive, automatically detecting and adjusting to various agile methodologies like kanban, scrum, story points, or ticket counts.

A team using Mission Control, it has detected the Scrum methodology and fibonacci story pointing.

Once a team is registered in Mission Control, the platform generates a comprehensive overview, providing everyone with access to performance metrics, roadmaps, target delivery dates, delivery projections, and a wide range of other valuable insights.

Showing a list of teams registered with the Mission Control deliver platform, including their detected methodology.

If you are curious to try out the team experience, you can onboard using Jira Cloud in less than 2 minutes and see for yourself for free.

Step 2: Building the Delivery Picture Between Teams

This is where most existing tools fall short, but where Mission Control excels. Traditional tools often focus solely on individual team performance, leading to local optimisation. However, the real issues for large organisations operating agile at scale lie above the team.

To address this, we offer a free trial for up to three teams per organisation. We believe that the major challenges start at this step, making it crucial to gain a broader perspective.

The transformation at this stage involves shifting the focus from individual teams to the entire delivery ecosystem, ensuring a holistic view of performance and collaboration.

Representation of the connections Mission Control tracks between teams and the organisations projects

This is why Mission Control has been developed as a unified, transparent delivery platform accessible to everyone in your organisation. It cuts through the noise, allowing anyone to view performance, roadmaps, and projections for all teams and projects. This holistic view helps everyone see the big picture, making performance and delivery issues clear and empowering the organisation to make data-informed decisions. It also provides a positive form of peer pressure to ensure that teams keep their backlog/roadmap/performance in an acceptable state, according to the chosen set of governance rules for teams in an organisation.

With team-level performance and delivery easily inspectable, we can begin tracking interactions between teams. Leaders can identify areas of struggle and bottlenecks, track dependencies & coupling between teams, and gain a comprehensive understanding of their delivery ecosystem’s landscape.

Tracking historicl dependencies between teams in Mission Control to understand interactions

Step 3: Revealing the Strategic Picture

The reality is that a multi-team feature can only ship as fast as the slowest team can deliver. From the perspective of delivering value to the customer quickly, optimising areas outside the main bottleneck adds no value. In fact, it can worsen the situation by further overloading the bottleneck. This is a fundamental principle of the theory of constraints.

After achieving clarity at the team level and examining interactions between teams, the next step is to build a clear strategic picture. This involves defining a light weight process to visualise and track strategic work from a top-down perspective, ensuring alignment and coherence across the organisation. This process should be automatic and instant to give leaders the most up to date view possible, so they can use this information to act.

An demo showing initiative tracking in Mission Control, grouping work between teams and conducting forecasting.

Most organisations can build some sort of process to achieve this, but it is often difficult. It typically involves very expensive tooling (like Jira Align, Big Picture, etc.), which operate in a top-down, rigid model, or it leads to a significant increase in bureaucracy.

The incredible costs for Jira Align, Atlassian’s SAFe solution to building a strategic view

This inefficiency often manifests as large steering/status update meetings, manually updated roadmaps/Gantt charts, and the manual collection of status updates from teams.

So, what is the solution? With the team level sorted, efforts should focus on building proper governance around tracking strategic initiatives. This involves establishing a simple set of rules to sensibly group work between many teams in tools like Jira.

With these rules in place, Mission Control can build a clear and comprehensive view of strategic initiatives. It runs delivery projections, tracks scope increases, and acts as a tool to help keep everything on track.

Conclusion

In conclusion, transforming your software delivery ecosystem to be more automated, transparent, and data-driven involves progressing through three key stages: building strong foundations at the team level, constructing a comprehensive view between teams, and then revealing the strategic picture. Mission Control is designed to facilitate this transformation by providing an intelligent, adaptive platform that supports various agile methodologies, ensures a unified and transparent delivery ecosystem, and offers strategic insights to optimise delivery performance. By following these steps and leveraging Mission Control, organisations can achieve significant cost savings, enhanced performance, and seamless delivery of value to their customers.

Ready to take your organisation to the next level? Onboard your team with Mission Control today. Experience the benefits of a truly data-informed delivery platform. Get started with a free trial and see the difference it can make in just 2 minutes.

3 Simple Reasons Your Organisation Struggles with Data (+ How to Fix It)

In today’s data-centric world, teams aim to leverage their data to enhance performance and decision-making. Despite the abundance of data, many struggle to use it effectively. This post explores three hidden barriers and offers practical solutions to overcome them, guiding your team towards data-informed success.

Barrier 1: Mindset

The journey to effectively utilising delivery data begins with cultivating the right mindset, a challenge that is often extensive and complex. Approaching data with an open and critical perspective is crucial, and this idea is encapsulated perfectly by statistician George Box’s famous quote:

When Box speaks of a “model,” he refers to any representation of reality, ranging from a mathematical algorithm on a chalkboard to a digital Kanban board on your screen. These models serve as tools, simplifying complex realities to help us make sense of them.

a Monte Carlo ‘model’ predicting delivery dates for a backlog in our software delivery platform Mission Control

Recognise the limitations of your models and datasets. Be scientific in your approach: focus on ranges, observe trends, and weigh probabilities. Remember, the goal is not to find a perfect model but to find a useful one.

In Summary: Cultivating a Healthy Skepticism

Encourage your team to approach data with curiosity and a critical eye. Embrace the uncertainty, and learn to find the balance between skepticism and trust in the data.

Barrier 2: Grasping the Situation

In today’s challenging economic climate, leveraging data effectively is paramount for boosting performance, anticipating outcomes, honing decision-making, and driving unparalleled results. Understanding the decision-making spectrum, ranging from instinctive and swift to deliberate and data-driven, is crucial.

Inspired by George Box’s insight that “all models are wrong, but some are useful” our infographic serves as a navigational tool to pinpoint your organisations position on this spectrum.

      • Left Spectrum: Decisions are intuition-based, quick, and low-cost, albeit with potentially lower impact. For instance, a Startup Founder rapidly adapting to market changes.

      • Right Spectrum: Here, decisions are data-driven, meticulous, and costly in terms of time and resources, but their potential impact is monumental. Consider NASA’s work on the James Webb Telescope, where decisions undergo exhaustive analysis.

      • Speed & Cost: Movement from left to right corresponds with a decrease in decision-making speed and an increase in associated costs.

      • Current Technological Limits: The far-right boundary highlights the present limits of technology in decision-making, showcasing the maximum extent of data-informed deliberation currently possible.

    Adapting with Technology

    Advancements in cloud technology, automation, machine learning, AI, and data analytics are reducing the cost of data-informed decision-making, making it increasingly accessible. Recognise your place on this spectrum and, if necessary, arm your team with the appropriate tools to navigate this landscape effectively and fully utilise available data.

    Barrier 3: Philosophy

    Understanding the philosophy that your team and organisation hold towards data is crucial, as it forms the foundation for how metrics and KPIs are perceived and utilised. Unfortunately, it’s not uncommon for companies to misstep in this area, using metrics as a tool to exert pressure on their staff rather than a resource for, understanding, growth and improvement.

    Belief in Metrics: A Cornerstone

    Reflecting on the wisdom shared in ‘The Tyranny of Metrics‘, we grasp a fundamental truth:

    “Those engaged in the act of being measured must believe in its efficacy.”

    Jerry Z. Muller

    In essence, belief is paramount. Without faith in the metrics and KPIs at play, individuals may manipulate results, diminishing the authenticity and value of the data.

    A prominent example, albeit region-specific, is witnessed within the UK’s National Health Service. Government-imposed targets on waiting times led hospitals to manipulate patient intake by leaving them in ambulances longer, prioritising statistical compliance over genuine patient care.

    Looking beyond specific regions, consider a global corporation aiming to boost productivity. If metrics imposed do not resonate with employees, the results may be skewed, mirroring the NHS scenario on a corporate scale.

    It’s imperative for organisations to select industry-standard metrics that resonate with their teams. In software development, for instance, prioritising lead, cycle time and DORA metrics over lines of code and commit numbers proves more effective and credible.

    In closing, while metrics serve as a vital tool in navigating the complex world of data, we must not lose sight of our ultimate goal: delivering unparalleled value to our customers. The metrics we choose, and the belief our teams place in them, play a pivotal role in achieving this paramount objective.

    Conclusion

    While data insights are a vital tool, our ultimate goal is to deliver unparalleled value to our customers. By cultivating a data-informed mindset, understanding your decision-making landscape, and fostering a positive philosophy towards data, you can unlock the true potential of delivery data. These strides empower teams to enhance performance, make informed decisions, and ultimately drive success.

    Ready to take your team’s data-informed journey to the next level? Subscribe to our newsletter for regular updates, expert insights, and practical tips. Transform the way you use data, turning hidden barriers into stepping stones for success.

    Get in Touch

    Please feel free to contact us via email or book an appointment.

    Email us on:

    info@methodshift.co.uk

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