3 Eye-Opening Reasons Your Agile Organisation Struggles with Data (and How to Fix Them)

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.


    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.

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