About Wireless Logic
Wireless Logic – IoT connectivity for any device, anywhere
Wireless Logic is a global leader in Internet-of-Things (IoT) connectivity, dedicated to bridging the physical and digital worlds with seamless, secure, and scalable solutions.
With more than 14 million devices connected across 165 countries and direct partnerships with 50+ mobile and satellite operators, they offer global coverage and end-to-end IoT services which accelerate the success of IoT projects.
Conexa, a purpose-built platform and dedicated IoT network, enables customers to securely connect and manage assets across any network and any number of deployments. This simplifies operations, accelerates time to market, lowers the total cost of ownership, and ensures ultra-reliable connectivity.
Their IoT services are meticulously designed, tested, deployed, and managed to meet the specific needs of each customer device fleet. They strive to deliver the most reliable, flexible, and secure connectivity services in the market.
Wireless Logic's customers range from global enterprises and governments to startups and SMEs, and they operate across a wide range of market sectors, including agriculture, healthcare, manufacturing, security, transport, energy, utilities, and smart cities.
Backed by Montagu, a leading mid-market private equity firm, Wireless Logic benefits from unrivalled financial strength and continued investment in growth and innovation.
Introducing Susan Ridgeon and her role within Wireless Logic
Susan has been a Scrum Master at Wireless Logic for two and a half years, playing a pivotal role in guiding her teams toward better processes and outcomes. With her experience spanning over five years in Agile practices, Susan brings expertise in fostering realistic planning and continuous improvement, even amidst the challenges of rapid company growth.
Coming from a Microsoft Azure environment, Susan faced an initial challenge adapting to Atlassian and Jira upon joining Wireless Logic. Early on, she realized the limitations of out-of-the-box Jira reports, especially for metrics like Cycle Time. In her role, she actively works to optimize Wireless Logic’s use of tools like Jira and integrate probabilistic forecasting methods to drive better delivery accuracy.
Background
Wireless Logic started using ActionableAgile® Analytics in Jira Cloud in mid-2023 as part of their overhaul to move away from time-based estimates. While working in three-week sprints, probabilistic forecasting has since proved to be not only more accurate but also a better fit for Wireless Logic’s growing needs.
The Situation
Wireless Logic faced a critical challenge: shift away from outdated time-based estimation methods that led to over-optimistic, unrealistic plans. This challenge was deeply felt by teams composed of Technical Leads, Technical Product Managers and Engineers, who, despite best efforts, often failed to complete deliverables and meet expectations.
One of the biggest pain points Susan faced was the “false sense of accuracy” that reinforced the reliance on time-based estimates. Though developers were eager to move away from this approach, alternatives like story points posed their own challenges. There was a lot of mis-understanding surrounding story points and the lack of usability as a delivery date.
As the company recognized the need to prioritize more realistic planning and foster a culture of continuous improvement, Susan embarked on a mission to introduce approaches, like probabilistic forecasting with ActionableAgile® Analytics, to align the teams’ goals with achievable outcomes.
Along with ActionableAgile® Analytics, T-Shirt sizing proved more suitable for the team to help shape the conversations and drive discussions.
Limited Visibility and Manual Efforts
To bridge the gap, Susan started conducting her own experiments. After starting a free trial of ActionableAgile® Analytics, Susan would compare the teams time-based estimates to the forecasts provided by the Monte Carlo simulations from ActionableAgile® Analytics.
Susan vividly recalled a pivotal sprint where one of the teams planned 20 tickets but managed to deliver only nine. In the background Susan had used the Monte Carlo simulation which forecasted that the team would complete 10 tickets—accurately reflecting the outcome.
This result highlighted the inadequacies of their time-based estimation approach and underscored the value of probabilistic forecasting.
Another challenge was extracting critical metrics like Cycle Time from Jira. “It’s just really hard to get that information from Jira,” Susan explained:
Implementing ActionableAgile® Analytics - What happened after?
The implementation of ActionableAgile® Analytics at Wireless Logic was a straightforward process. Susan built a business case highlighting the tool’s potential to improve accuracy and efficiency, which gained buy-in from the Technical Leads and the Engineering Manager. The team started out with approval for a monthly subscription before moving over to an annual subscription in February 2024.
During the initial phase of the rollout of ActionableAgile® Analytics, Susan recalled an experience seeking assistance for a few technical questions which required some assistance from the support team at 55 Degrees. “Your support team are amazing—feel free to include that in your post! They’re so responsive, getting back to me quickly and even setting up a call with more of the team when we run into an issue. Truly impressive service!"
The Rollout – One Sprint team at a time
When Wireless Logic decided to implement ActionableAgile® Analytics it was decided to roll it out team by team. Initially this began with one sprint team which were chosen due to their experience and capacity.
After proving success with this team, the tool was expanded to other teams one by one. During the rollout, Wireless Logic primarily used three main charts: Aging Work in Progress, Cycle Time Scatterplot, and Monte Carlo ("How Many").
ActionableAgile® Analytics is now used during retros – During which the team will look at the data from the Cycle Time chart and look for any outliers. This helps the team break down where work stalled which initiates valuable conversations.
Conversations which are not to drive blame, but to actively seek improvements – The team tries to understand if there were any lessons learnt and if they could have done anything different to formulate actions for improvement to take forward.
“On occasions we have aging work, we will review in the daily scrum as the app visualises it much better than anything we get in Jira. It then helps teams to know where to focus efforts, prioritise and make their daily plan.
Engaging Teams and Encouraging Discussion
To facilitate the rollout of ActionableAgile® Analytics, Susan conducted internal workshops focused on flow metrics such as Work Item Age and Cycle Time. “I’ve been showing the teams how to get the information and explained why it’s important for Daily syncs” she shared.
These efforts also prompted a cultural shift in how teams approached estimation. Inspired by insights from meetups and Monte Carlo simulation results, Susan introduced T-shirt sizing as another discussion point to complement estimates from ActionableAgile® Analytics—a strategy to spark more dialogue.
“We also use T-shirt sizes now. If someone says large and someone else says small, that starts a conversation, it encourages discussion and shared understanding. The conversation that follows helps uncover hidden complexities, risks, or gaps in knowledge, leading to a more accurate shared understanding of the task. ”
This change helps to identify where they can split tickets into smaller chunks of work. Perhaps the most significant outcome was the cultural change within the teams. Susan described a shift in focus from starting new tasks to finishing work in progress:
The Result
A Shift to Realistic Planning
Implementing ActionableAgile® Analytics has transformed Wireless Logic’s planning approach, leading to more achievable commitments. Susan highlighted this shift: “We are more likely to finish everything that we’ve committed to in planning than we were before. The data is much more realistic, and we’re not overplanning like we used to.”
With Monte Carlo simulations, teams now base their plans on throughput and capacity, resulting in plans that align more closely with their actual delivery potential.
Fostering a Culture of Finishing
The cultural shift toward completing work rather than starting new tasks has been a standout result of using ActionableAgile® Analytics. Susan noted the change in team conversations: “Stop starting, start finishing. That became the focus. It was really positive to see tech leads and team members championing this mindset.”
One team lead exemplified this change, encouraging the team to prioritize completing aging work instead of pulling in more tasks. By comparing the same day a year apart Susan explained the Work In Progress was 20 a year ago and now the team has 5 items in progress. This focus has made the work more manageable with less risk.
Empowering Teams with Insights
The adoption of actionable data through metrics like WIP aging and cycle time has driven meaningful conversations in retrospectives and daily scrums.
By incorporating these insights, teams are improving their processes and gradually achieving greater efficiency and predictability.
“With the flagged option in ActionableAgile® Analytics, we can easily identify delays in our workflow. For instance, when reviewing cycle time, we can see that a task was blocked for 10 days and investigate the reasons behind it. This insight helps us address bottlenecks and improve our processes”.
Summary of Outcomes
Increased Predictability
Improved Collaboration and Focus
Streamlined Data Insights
Increased Focus on Prioritization
Structured Conversations
What Does the Future Look Like for Wireless Logic?
Integration of ActionableAgile® Analytics into the business
Wireless Logic is exploring opportunities to expand the use of ActionableAgile® Analytics beyond its current teams to create a unified approach across the business. While the tool has already driven significant improvements in planning and collaboration within engineering and Dev Support teams, Susan sees potential for wider adoption.
“We’re still working on encouraging more teams to use the tool. Everyone has access, but it’s mainly myself and our other Scrum Master, who are actively leveraging it,” Susan explained.
By embedding flow metrics and data-driven practices across all teams, Wireless Logic aims to foster a culture of transparency and shared accountability.
Using Sprint Lengths for Monte Carlo Forecasting
While using Monte Carlo Forecasting within the app, Susan encountered a challenge related to her team's sprint-based approach. Her teams currently work in 3-week sprints, which means throughput data is only updated at the end of each sprint. As a result, forecasting based on recent data can be difficult, since the ActionableAgile® Analytics Monte Carlo model relies on a continuous flow of completed work.
Ideally, Susan and her team would be able to generate forecasts in the context of their sprint cycle, rather than being constrained by a time-agnostic approach. However, Monte Carlo Forecasting is primarily designed for workflows with steady, incremental throughput—like Kanban—rather than batch-based sprint systems.
Since providing this feedback, 55 Degrees has now put this on our public roadmap (See the Under Consideration tab - “Forecast by additional time units” – If this is a feature you would like to see added you can view the roadmap of ActionableAgile® Analytics here and vote on features such as this that you would like incorporated into the app.
