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Month: June 2026

Fletcher Jones Case Study

Fletcher Jones

Written by Regine Wilber on . Posted in Machine Learning & Data Science.

Fletcher Jones – Predictive Analytics for Car Sales

Fletcher Jones, a renowned automotive retail company, faced the challenge of predicting car sales and integrating desirability with inventory levels. They lacked visibility into which cars were most likely to sell, impacting price setting, sales tactics, inventory management, and purchasing decisions. They needed a solution to optimize their business plan goals and make data-driven decisions.

Leveraging historical data, predictive models analyzed car features and time on lot to predict sales likelihood, informing decision-making.

To address the customer’s problem, historical data was leveraged to build predictive models. These models analyzed car features and their influence on the time a car spent on the lot, providing insights into sales likelihood. Feature importance analysis helped determine the most influential car features. The predictive output was integrated with inventory and sales data, enabling informed decision-making to support business objectives.

Data Science Methodologies employed:

  • Time-series analysis to predict car sales over time.
  • Decision Trees to identify feature importance for sales likelihood.

Leveraging data science and integrating predictive analytics transformed their operations.

The implementation of predictive analytics had a profound impact on Fletcher Jones’ operations and profitability. The outcomes achieved were as follows:

  • Increased profit margins: By accurately predicting sales likelihood, Fletcher Jones was able to optimize price setting and discount flexibility, leading to improved profit margins on car sales.
  • Decreased inventory cost: With insights into the likelihood of a car selling and the influential features, Fletcher Jones could effectively manage inventory levels and avoid excessive stock, reducing inventory costs.
  • Improved business planning: The predictive models supported better pacing and determination of hitting business plan goals. Fletcher Jones could align their inventory with business objectives, ensuring the availability of cars that would meet sales targets.

By leveraging data science methodologies and integrating predictive analytics into their decision-making processes, Fletcher Jones transformed their operations. The ability to predict car sales and understand the impact of specific features empowered them to make strategic decisions, maximize profitability, and optimize inventory management.

Overall, the implementation of predictive analytics enabled Fletcher Jones to stay ahead in the competitive retail industry, providing valuable insights that positively impacted their bottom line while maintaining their reputation as a leading automotive group.

EG Business Matrix

EG Business Metrics

Written by Regine Wilber on . Posted in Machine Learning & Data Science.

EG Business Metrics, a Financial start-up interested providing predictive analytics to understand risks associated with investment

EG Business Metrics, a finance industry start-up, aimed to provide predictive analytics to identify operational risks associated with investment firms. The challenge was the vast and complex nature of these risks, requiring manual effort to sort through data and identify key information. The existing process lacked confidence and needed a solution to automate risk assessment and provide actionable insights.

Working with Calligo’s data scientists to develop several powerful methodologies

To address the customer’s problem, EG Business Metrics partnered with Calligo’s data scientists to develop several models and methodologies. They sought answers to various questions such as indicator correlations, outcome correlations, dimension reduction, complex correlations, candidate indicator importance, and handling contradictory signals in the data. These models were used to derive metrics and custom exploration tools, enabling a confident evaluation of investment firms.

Data Science Methodologies employed:

  • Data Science by Design: Applying data science principles to solve the specific challenge.
  • Principle Component Analysis: Reducing the dimensionality of the indicator set.
  • Multiple Correspondence Analysis: Analyzing categorical data and correlations.
  • Correlations and Canonical Correlations: Assessing relationships between indicators.
  • Clustering: Grouping investment firms based on similarities.
  • Custom Mathematics: Developing algorithms tailored to EG Business Metrics’ needs.
  • R-Shiny: Creating interactive exploration tools for customized evaluation.

Calligo’s Data Science team had a significant impact on EG Business Metrics’ business.

The implementation of predictive analytics and custom exploration tools had a significant impact on EG Business Metrics’ business. The outcomes achieved were as follows:

  • Viability assessment: The algorithms and tools became the central element of EG Business Metrics’ business, enabling them to confidently assess the viability of investment firms. They automated the process of identifying and flagging operational risks, saving time and improving accuracy.

The solution empowered EG Business Metrics’ clients, providing them with insights to select and monitor investment firms effectively. By leveraging predictive analytics and data science methodologies, EG Business Metrics transformed their business, offering a management toolkit that combined data, analytics, and practical experience to measure, monitor, and modify controls programs.

Overall, Calligo’s solution for EG Business Metrics’ not only addressed their customer’s challenge of operational risk assessment but also established them as a trusted partner in the finance industry, empowering their clients to make better-informed decisions and mitigate risks effectively.

Wheels Up Case study

Wheels Up

Written by Regine Wilber on . Posted in Data Analytics & Visualisation.

Calligo supported Wheels Up with data-driven decision-making to improve customer experience, forecasting, cost savings, and time efficiency.

Wheels Up – a US private jet charter company – is on an exciting growth journey. But with more than 11,000 active members and counting, 55,000 flights a year, record sales and acquisitions to boot, its heady success was throwing up some curveballs. A lack of data-driven decision-making was fast-becoming its Achilles’ heel. It was time to support its sales, revenue management and finance teams with much greater visibility; data that would supercharge customer experience, ignite efficiency internally and boost burgeoning sales figures and profits.

Calligo built data dashboards for Wheels Up’s sales, revenue management, and finance teams to provide 360-degree visibility of customer portfolios and measure performance.

To put data-driven decision-making at the epicenter of Wheels Up’s business model, we built effective analytical tools, data dashboards and skill sets for Wheels Up’s sales, revenue management and finance teams. Here’s a snapshot of how we supported their sales department.

A data dashboard needed to give the sales team 360* visibility of its customer portfolios. What flights has he or she booked? What routes were popular? Have there been any hiccups? With a click of a button, a Wheels Up Account Manager now has a holistic overview of each existing member. Any action the client has taken, right there in real-time – accompanied by an ability to look after them better than ever. And informed perspective during account renewal discussions. Internally, we also created a dashboard that measured performance, analysing things like retaining clients, renewing contracts, and managing deposits.

Calligo’s dashboards had immediate benefits to Wheels Up: personalised customer experience, data-driven forecasting, cost savings, and saved time.

The impact of our dashboards has been immediate and incredibly beneficial, both financially and operationally, to Wheels Up. Here are some of the gamechangers:

  • Sales: customers now have an ultra-personalised experience, benefitting from savings, offers, and a feeling of being individually valued.
  • Revenue management: pricing is no longer based on trend, but accurate data-driven forecasting – allowing for proactive planning ahead based on demand.
  • Finance: $100,000s of estimated savings will be made from Calligo’s data revealing how much credit card processing fees were costing. These payments will no longer be accepted.
  • Across the business: hours and hours have been saved each week finding out information about customers, pricing, and profit-making activities.

Up next, Calligo will continue to empower Wheels Up with data-driven decision-making in other departments such as marketing, operations, and maintenance.

Chipper Cash case study

Chipper Cash – Global Payment Network Fraud Detection​

Written by Regine Wilber on . Posted in Machine Learning & Data Science.

Chipper Cash faced a critical challenge in combating fraudulent activities

Chipper Cash, a global payments network, encountered a significant challenge in detecting and mitigating fraudulent activities within its platform. The complexity of its account structures, diverse use of multiple currencies, and connections with financial institutions in less-regulated regions posed a heightened risk of fraudulent transactions. The potential impact of fraud could swiftly spread across thousands of accounts, threatening the integrity and trust of the entire network.

We developed a network analysis solution for proactive fraud detection

To address this challenge, we developed and implemented a robust network analysis solution tailored to Chipper Cash’s unique ecosystem. Our approach involved leveraging advanced link analysis and statistical techniques to swiftly identify and assess flagged fraudulent activities. By analyzing the relationships between accounts, individuals, and institutions within the network, we could pinpoint other linked entities at risk of fraudulent behavior.

Key to our solution was the identification of fraudulent transactions associated with multiple accounts across diverse institutions, which often traced back to a small set of users. These transactions were promptly flagged to enforcement teams for further investigation or imposition of freezes, preventing the proliferation of fraudulent activity and minimizing business losses.

The implemented solution transformed fraud detection and mitigation for Chipper Cash

The implementation of our network analysis solution transformed Chipper Cash’s ability to detect and mitigate fraudulent activities effectively. By proactively analyzing network connections and identifying suspicious patterns, the platform could swiftly respond to emerging threats, safeguarding the integrity of the payment network and protecting the interests of its users.

Our solution empowered Chipper Cash’s enforcement and recovery teams to focus their efforts strategically, targeting high-risk accounts and entities within the network. This proactive approach not only minimized the financial impact of fraud but is also bolstering trust and confidence among users and partner institutions.

sustainable fisheries

Sustainable Fisheries Partnership

Written by Regine Wilber on . Posted in Data Analytics & Visualisation.

Sustainable Fisheries Partnership sought Calligo’s help to visualise data solutions to prevent bycatch of ocean wildlife in commercial fishing at Seafood Expo.

It was a month before Seafood Expo North America, the leading trade event for seafood buyers in every market category.

Sustainable Fisheries Partnership had new research with data and solutions of how to prevent and reduce the catch of ocean wildlife – sharks, seabirds, marine mammals, and sea turtles – in commercial fishing. “Bycatch,” the catch of non-target species, is the biggest single threat to the sustainability of marine fisheries.

The trade show provided a pivotal opportunity to tangibly show the best solutions for addressing bycatch problems to hundreds of retailers, seafood companies, and fisheries stakeholders. For example, if longline fisheries were having trouble with seabirds grabbing bait and getting hooked, what could they do? Sustainable Fisheries Partnership had the answers to these problems in their data. But the solutions were buried in reports and not easy to see for users.

Sustainable Fisheries Partnership looked to Calligo to visualize the answers hidden in the data and help them make a splash at the trade show.

Calligo helped Sustainable Fisheries Partnership refine their data, using Alteryx to clean and visualise the data into Tableau for users.

Calligo worked with Sustainable Fisheries Partnership to investigate their data sources.

The data was in a single-source database and was mostly clean. However, there was a large quantity, and Sustainable Fisheries Partnership needed Calligo’s help to refine and tease out what aspects of the data end users would be most interested in.

Calligo used Alteryx to extract and clean up the data, and then loaded it into Tableau to produce data visualizations for Sustainable Fisheries Partnership’s users.

The Solve My Bycatch Problem tool allows end users to see various factors, such as effectiveness, implementation, and cost, and evaluate the pros and cons of different strategies and methods to find the best solutions for their specific wildlife interaction problem(s).

All the visualizations were completed quickly and delivered on time.

Our Solve My Bycatch Problem tool is a resource for fisheries stakeholders to understand how to reduce risk to vulnerable ocean wildlife. But it’s only really valuable if people use it. The eye-catching design and easy user interface that Calligo created will help ensure that the right people get the information they need.

Kathryn Novak, Sustainable Fisheries Partnership

The Solve My Bycatch Problem tool was presented at Seafood Expo and received positive feedback. Sustainable Fisheries Partnership plans to make it accessible on mobile.

The Solve My Bycatch Problem tool was unveiled at a Bycatch Solutions event at the Seafood Expo, and was highlighted as one of the new initiatives in seafood sustainability in a story by Progressive Grocer.

The tool was presented on screens at the event at Sustainable Fisheries Partnership’s booth on the trade show floor, allowing for hands-on experience. The data visualizations and tool were well received, and Sustainable Fisheries Partnership’s end users loved the display.

Sustainable Fisheries Partnership stood out from the crowd, with a data-based tool that users could interact with and access to solve their crucial issues – and showed people the power of their dataset.

Next up, the project will center around making the data and tooling accessible on mobile, to support the 25 to 30 percent of users who access the Sustainable Fisheries Partnership website via mobile devices.

Holcim case study

Holcim

Written by Regine Wilber on . Posted in Data Analytics & Visualisation.

Holcim – Driving Data-Driven Growth in Construction

The Holcim Group is a Swiss-French multinational company that manufactures building materials. It has a presence in around 70 countries, and employs around 72,000 employees.

Holcim’s executive team recognized the need for data analytics to drive business decisions and achieve their growth targets. They faced challenges in analytics bandwidth and expertise, prompting the director of strategy to seek external support. The client aimed to implement best practices in analytics, enhance data literacy, compete against competitors, and drive acquisitions as they targeted a revenue increase from $2B to $4B.

Calligo partnered with Holcim, delivering data-driven solutions and building an analytics foundation.

Calligo partnered with Holcim to deliver data-driven solutions and build an analytics foundation. They created visual dashboards, including market share dashboards to aid acquisitions and identify external growth opportunities. A daily sales report was also developed to guide go-to-market strategies. Calligo’s consultant played a vital role in growing the internal analytics team to three members and provided leadership in strategy and technology scaling through recent acquisitions. The partnership aimed to expand further by introducing data partners like Snowflake to optimize the data ecosystem and accommodate future growth.

Technologies Deployed:

  • Alteryx: Data integration and analysis platform.
  • Tableau: Data visualization tool.

Calligo Practices:

  • Data Analysis: Utilizing analytical techniques to extract insights from data.
  • Data Integration: Combining and transforming data from various sources.
  • Data Visualization: Creating visual dashboards for intuitive data representation.

The implementation of data analytics transformed Holcim

The implementation of data analytics had a significant impact on Holcim’s operations and growth strategy. The outcomes achieved were as follows:

  • Time-saving: The finance and departments team saved 10 hours per week in data work, enabling them to focus on more strategic tasks.
  • Acquisition support: The analytics solutions aided the acquisition strategy of both the parent company and recent acquisitions, facilitating informed decision-making.
  • Revenue growth: The daily sales strategy, supported by data-driven insights, contributed to the goal of increasing revenue from $2B to $4B, achieving a Compound Annual Growth Rate (CAGR) of 14.87%.

By leveraging the power of data analysis, integration, and visualization, Holcim transformed into a more data-driven organization. The collaboration with Calligo not only delivered impactful solutions but also paved the way for further expansion and optimization of their data ecosystem. Holcim positioned itself to compete and differentiate in the construction industry, equipped with the tools and expertise to drive growth and make data-driven decisions at every level.

Microsoft Azure case Study

Microsoft Azure Growth & Adoption

Written by Regine Wilber on . Posted in Machine Learning & Data Science.

Microsoft needed a solution to streamline and enhance its Sales Plays

Microsoft faced challenges in updating its Sales Plays around key Azure technology each year. The existing process, relying on subjective assessments from SMEs, took months and lacked data-driven insights. Definitions for Sales Plays changed throughout the year, making tracking effectiveness challenging. Microsoft needed a solution to streamline and enhance the Sales Plays process while providing consistent year-over-year tracking.

Calligo built models for various Sales Plays

In collaboration with Calligo, Microsoft implemented a dynamic solution using R Shiny. The tool empowered the Data Science team to build models for various Sales Plays, optimizing the process and enabling more informed decision-making. The solution included:

  • Elastic net regression to identify predictive features for each target.
  • Controls for reducing collinearity via lasso and ridge regressions.
  • Boosted random forest model predicting service adoption or usage increase.
  • Post-processing with cosine similarity to target accounts for growth or adoption.
  • Visualization of model outputs in Power BI reports for easy seller access.

The difference working with Calligo was the team’s mindset. They looked at the problem entirely as a commercial question, not as a data science challenge applied in a business context. And it worked.

Bo Oslen, Microsoft

A transformative impact on Microsoft’s Sales Plays

The implementation of the solution had a transformative impact on Microsoft’s Sales Plays and data-driven decision-making:

  • Efficiency Gains: Empowered the data science team to build dozens of models efficiently, a process that would have been manual and time-consuming.
  • Enhanced Accuracy: Account targeting for new services saw a significant increase in accuracy, from 10% to 40%, outperforming the prior method. The average expected adoption of a new service rose to 3%.
  • Revenue Growth: Accounts targeted for growth achieved an average YoY growth of 17%, surpassing the previous model’s 11% and the overall average of 7%.
  • Reduced Cycle Time: Targeting logic time was reduced from a 4-month cycle to just 2 weeks, enabling quicker and more agile decision-making.

In summary, the collaborative effort with Calligo empowered Microsoft to revolutionize its Sales Plays, leveraging data science for efficient model building, accurate targeting, and accelerated growth, ultimately optimizing the entire process and driving substantial business impact.

Sealy Logistics and Sales Case Study

Sealey

Written by Regine Wilber on . Posted in Data Analytics & Visualisation.

Sealey – Sales and Logistics Insights

Sealey, a prominent UK-based global retailer of professional tools and workshop equipment, faced a complex challenge due to their extensive product range, serving over 70 countries and providing access to more than 12,000 products and over 5 million spare parts through their network of dealers. The company experienced fluctuations in buying patterns based on seasonal trends and needed to forecast purchasing demands more accurately.

To address these challenges and enhance their sales and logistics performance, Sealey recognized the need to introduce an analytics capability that would provide insights into their sales and supply chain operations. They sought to understand how data could empower their decision-making, uncover missing data elements critical to their roles, identify opportunities they were unaware of, and optimize their internal data analytics capabilities. Additionally, they aimed to achieve cost efficiencies by transitioning from disparate point solutions to a more comprehensive data architecture.

Calligo transformed Sealey’s data capabilities through assessments, data opportunities, efficient architecture, vision, performance dashboards, and logistics insights.

Calligo engaged with Sealey to address their business needs and delivered a comprehensive solution that transformed their data and analytics capabilities. The engagement included the following key components:

Data Consumer Assessments: A thorough evaluation of how different teams and individuals within Sealey used existing data and how it influenced their decision-making. This analysis uncovered the missing data elements essential for their roles and identified opportunities for improvement.

Data Opportunities: Exploration of generative or derived data opportunities that were previously undiscovered. This process aimed to unleash the potential of data for Sealey’s growth and efficiency.

Cost-Efficient Data Architecture: Development of a strategy to streamline data architecture by replacing point solutions with a holistic approach. This not only reduced operational complexity but also optimized the use of resources.

Art of the Possible: Building a vision of what could be achieved with the insights gained from the discovery phase. This allowed Sealey to understand the full potential of their data analytics capabilities.

Hierarchical Performance Dashboards: Creation of dashboards that provided insights at different levels of the organization’s hierarchy, supporting effective management reporting. These dashboards enhanced decision-making and allowed for real-time tracking of sales and logistics performance.

Logistics Capacity Planning Insights and Order Fulfillment Alerting: Utilizing advanced data analytics methodologies to provide insights into logistics capacity planning and alerting mechanisms for order fulfillment.

We are pleased to recommend Calligo for their outstanding PowerBI proficiency and seamless cloud computing services. Their expertise in understanding and transforming our data into actionable insights has been invaluable, creating dashboards to aid our business processes and provide our sales and import teams with mission-critical information. Their support team provides us with a reliable, efficient, and secure cloud infrastructure which underpins our B2B and B2C proposition. Calligo is a key partner in driving our data-driven success.

Tim Thompson, Operations Director, Sealey

Sealey’s data transformation enhanced culture, sales, logistics.

The transformation of Sealey’s data and analytics capabilities had a profound impact on the organization. The key outcomes of this initiative included:

Established Data-Driven Culture: Sealey now has a corporate culture where data-driven insights empower the workforce to plan their activities more effectively. Employees can align their efforts with company priorities, resulting in more efficient and productive operations.

Enhanced Sales Revenue: The insights gained from the performance dashboards have enabled Sealey to make informed decisions, leading to increased sales revenue. By understanding customer buying patterns and responding proactively, they have captured new sales opportunities.

Optimized Logistics Efficiencies: The logistics capacity planning insights and order fulfillment alerting mechanisms have improved the efficiency of Sealey’s supply chain. This has led to quicker order processing and enhanced customer satisfaction.

In summary, the data and analytics transformation undertaken by Sealey, in collaboration with Calligo, has not only established a data-driven culture within the organization but has also significantly improved sales revenue and logistics efficiencies, making Sealey more competitive in the global marketplace.

Cymer Case Study

Cymer Maximize Service Revenue

Written by Regine Wilber on . Posted in Machine Learning & Data Science.

Cymer faced a significant challenge in their reactive approach to part replacement

Cymer, a global leader in engineering, manufacturing, and maintaining lasers for chip production, faced a significant challenge in the reactive approach to part replacement. Responding reactively to part failures resulted in high costs, both in terms of machine downtime and customer dissatisfaction. The unplanned replacement of parts due to failure, rather than scheduled maintenance, incurred substantial expenses, often exceeding a million dollars per occurrence. Machine downtime not only translated into financial losses but also led to dissatisfied customers, further impacting the company’s bottom line.

Calligo sought to optimize the clients’ maintenance operations

In collaboration with Calligo, Cymer implemented a comprehensive solution to address the challenges of reactive maintenance and optimize their operations:

  1. Integrated Predictive Analytics: Calligo leveraged machine diagnostics to predict the lifespan of components using ARIMA Time-Series and Survival Curve Modeling. This allowed for accurate forecasts of potential failures.
  2. Demand Forecast Integration: Machine lifespan predictions were combined with customer demand forecasts using sophisticated Monte Carlo simulations, providing a robust basis for decision-making.
  3. Customized Predictive Models: Calligo incorporated customer-specific service and maintenance preferences into the predictive models. This customization enhanced the accuracy of predictions, aligning maintenance actions with individual customer needs.
  4. Proactive Service Planning: The integrated predictive models enabled Cymer to schedule machine services and maintenance before failures occurred. This proactive approach positioned the company to avoid machine downtime and enhance operational efficiency.

Data Science Methodology:

  • ARIMA Time-Series: Utilized for accurate time-series analysis to predict component lifespan.
  • Survival Curve Modeling: Implemented to estimate failure probabilities and optimize maintenance schedules.
  • Monte Carlo Simulation: Used for scenario modeling and demand forecast integration.
  • Markov Chain Modeling: Applied to analyze the transition of machine states over time.
  • Tree-based ML Modeling: Utilized for creating predictive models based on decision trees.

Significant positive impact on Cymer’s operations

The implementation of the proactive maintenance strategy with Calligo had a significant positive impact on Cymer’s operations and business outcomes:

  • Accurate Demand Forecasts: Demand forecasts achieved an average accuracy of 92%, leading to more meaningful service dates and efficient resource allocation.
  • Downtime Reduction: Machine downtime, estimated to cost millions of dollars per day, was reduced by upwards of 50%. This reduction not only optimized operational costs but also greatly increased customer satisfaction.
  • Inventory Management Optimization: The proactive approach facilitated better inventory management, resulting in significant cost reductions.
  • Estimated Financial Impact: The overall estimated impact amounted to millions of dollars per year, reflecting the substantial savings and increased revenue generated by the proactive maintenance approach.

In summary, Calligo’s collaboration with Cymer resulted in a transformative shift from reactive to proactive maintenance, leveraging advanced data science methodologies. This not only addressed the initial challenges but also positioned Cymer as an industry leader, optimizing operations, reducing costs, and enhancing customer satisfaction.

USAF Case Study

USAF Air Mobility Command

Written by Regine Wilber on . Posted in Data Analytics & Visualisation.

USAF Air Mobility Command – Logistics Optimization

The United States Air Force Air Mobility Command (USAF AMC) faced significant challenges with its self-built Tableau Server user interface, which led to a poor user experience. Users found it cumbersome to navigate, requiring excessive clicks to access essential information. Additionally, once users found the answers they needed, crucial supporting content and information for next steps were often scattered across different platforms, causing delays in decision-making and action. This poor user experience resulted in high levels of user friction and frustration, leading to low engagement and customer satisfaction levels.

Collaborative Efforts to Improve User Interface

To address these challenges, Calligo, in collaboration with Tableau, closely collaborated with USAF AMC stakeholders. Joint presentations were conducted to multiple stakeholders within the USAF, laying the groundwork for the project. Calligo facilitated multiple requirements-gathering sessions with USAF users to understand their specific needs and preferences. Based on these insights, Calligo built a custom test Embedded Portal, consolidating and redesigning the USAF AMC dashboards to streamline the user experience and provide easier access to essential information.

Throughout the process, Calligo and Tableau held 1-2 meetings per week with USAF stakeholders, ensuring alignment and feedback at every stage. Business justification meetings were held to strengthen the sponsorship internally, followed by product demonstrations to a wide range of USAF users. Final presentations were made to the US Department of Defense, emphasizing the project’s alignment with strategic objectives.

Enhanced User Experience and Stakeholder Satisfaction

The collaborative efforts between Calligo, Tableau, and USAF AMC stakeholders resulted in a significant improvement in the user experience for USAF AMC personnel. The redesigned Tableau dashboards and Embedded Portal reduced the number of clicks required to access information, making it easier and quicker for users to find answers to their everyday questions.

Moreover, the consolidation of relevant content and information within the portal facilitated faster decision-making and action, reducing delays. As a result, user friction and frustration decreased, while engagement and customer satisfaction levels improved. The successful project implementation not only addressed the immediate challenges but also strengthened the ongoing relationship between Calligo, Tableau, and USAF AMC, paving the way for future collaboration and innovation in enhancing data accessibility and usability within the organization.

red classics case study

Red Classic – Optimized Logistics Operations

Written by Regine Wilber on . Posted in Data Analytics & Visualisation.

How can organizations enable self-service?

Red Classic, a leader in transportation and fleet maintenance solutions, faced challenges in optimizing operations and enabling self-service capabilities. With data sources scattered and lacking a centralized platform, queries were complex, slow, and required advanced SQL skills. Routine requests consumed valuable time, leaving little room for higher-value work. Point-in-time analysis was manual and time-consuming, hindering insights production.

Implementing Streamlined Data Pipeline

Calligo provided a solution by streamlining the data pipeline. They consolidated data sources into a centralized, scalable platform, reducing administrative burdens. Native SQL access was introduced to support reporting tools, ensuring high performance for analytical workloads. Additionally, a persistent staging area was established to enable quick historical analysis with simple SQL code.

Thanks to Calligo, we can support the growing information needs of the business as we grow our offerings to the market. We could not be happier with Calligo’s consistently high level of professionalism, quality and customer service.

Operations Director, Red Classic

Enhanced Efficiency and Self-Service Capabilities

The implementation yielded significant business impact. Analytical query processing time reduced by up to 90%, accelerating insights generation. Historical point-in-time analyses, previously slow and manual, now offer dramatic time savings potentially worth millions. Business analysts can now access insights in one place without profound SQL knowledge, laying the foundation for self-service capabilities. Overall, the solution optimized operations, freed up valuable time, and empowered Red Classic to make data-driven decisions efficiently.

United Nations Case Study

United Nations Sustainability

Written by Regine Wilber on . Posted in Machine Learning & Data Science.

A Case Study in Enhancing UN Sustainability Goals

Calligo recognized the need to enhance the role of data in advancing humanitarian efforts aligned with the UN sustainability goals. We identified a lack of effective utilization of data in planning, validating, and optimizing investments in current programs. This raised concerns about the overall effectiveness of reaching the prescribed human goals set by the UN.

Unleashing Insights for Effective Program Planning

To address this challenge, Calligo embarked on a comprehensive approach. They began by reviewing the UN sustainability goals to identify which objectives could be better supported through data and machine learning (ML) methods. This involved identifying objectives with direct measures, indirect measures, limited data availability, or dependencies on changes in government policy. Once these objectives were identified, Calligo gathered relevant publicly available data and stored it on their system for further engineering and ML modeling.

Using data science methodologies such as Data Science by Design, XGBoost Decision Trees, Feature Importance analysis, and R-Shiny for visualization, Calligo developed ML models and visualizations to characterize child abuse on a global scale. These models aimed to determine the most effective programs to combat child abuse, providing valuable insights for planning and implementation.

Empowering Humanitarian Initiatives through Data-Driven Solutions

By leveraging data and ML techniques, Calligo’s solution had a significant impact on advancing humanitarian efforts aligned with the UN sustainability goals. The utilization of ML models and visualizations enabled a deeper understanding of the global landscape of child abuse. This understanding facilitated the identification of the most effective programs to combat child abuse, ensuring that resources and investments were optimally allocated.

Overall, Calligo’s approach helped bridge the gap between data, ML methods, and the UN sustainability objectives, providing clarity on how data can positively impact humanitarian efforts. By leveraging data-driven insights, organizations can make more informed decisions, drive meaningful change, and work towards achieving the prescribed human goals set by the UN.