Transforming Oil & Gas with Predictive Insights
SBI is a leading supplier and manufacturer of high-quality Oil Country Tubular Goods and Line Pipe for the oil and gas industry in both the United States and Canada.
During my engagement, I was introduced to prediction models and focused on data visualization. I used simulations to predict environmental and policy scenarios. Additionally, I provided help with engineering alignment and developed a single-case design system. It was an exciting project that required a lot of technical expertise.
The Challenge
How do we use business intelligence tools to interpret signals and gain insights into their sales and operational performance.
Driving Inventory Success
Within a mere 6 months, we successfully launched a V1 that exceeded client expectations. This enabled SBI to proactively engage with data-driven insights, leading to measurable improvements in inventory performance. I painted a clear picture of potential scenarios based on SBI's unique situation. This translated into actionable strategies like optimizing production schedules and proactively complying with new regulations, ensuring both financial and environmental sustainability for the future.
My Contribution
Data Visualization
Single Case Design System
Prototyping
Visual Design
Discovery & Research
Data Insights
My research delved into various aspects of inventory management, including:
Inventory turnover: This metric measures how efficiently a company sells and replenishes its stock. Analyzing trends to reveal areas for improvement, like reducing holding costs or optimizing production schedules.
Marketplace index: General economic conditions and consumer behavior relevant to the industry. Understanding market fluctuations to help anticipate demand shifts and adjust production accordingly.
Competitor analysis: Studying competitors' inventory strategies for valuable insights.
Purchase models: Analyzing historical purchase patterns helps predict future demand with greater accuracy, allowing optimization of stock levels and avoid stock-outs.
Maintenance Forecasting
Unplanned maintenance downtime can throw a wrench in the best-laid production plans. Delayed production leads to stock-outs, lost sales, and unhappy customers. To mitigate these risks, SBI needed to accurately forecast the impact of maintenance schedules on inventory levels:
Predictive maintenance: Implementing tools and sensors to anticipate equipment failures allows for scheduled maintenance, minimizing disruptions and maintaining consistent production.
Inventory buffer calculations: By factoring in maintenance schedules and lead times, we can calculate optimal inventory levels to ensure sufficient stock even during downtime.
Scenario planning: Modeling different maintenance scenarios and their potential impacts on inventory levels helps prepare for contingencies and adjust production plans accordingly.
Application Flow
Mapping out signals for Oil & Gas future, KPI's, and market activity. The layout helped dial in flow of supply chain and provided our first glimpse into the user navigation.
Bringing Data to Life
Collaborative brainstorming sessions with executives provided a valuable opportunity to visualize data in meaningful ways. Despite diverse layouts, rig counts emerged as a consistent focal point, signifying their importance in decision-making.
From Environment to Equipment Phase
Environment for example has certain soils that work for different types of equipment, if there is excess hydro carbons or contaminants these play a role in determining drilling location. For phases of production, it is policy for oil rigs to pass back data regarding what phase the equipment is in, or how much production is occurring.
Things change over the course of months to years, and this was what we wanted to capture in simulation.
Dashboard
Data-driven designs that brought insights to the forefront of the dashboard.
Wireframes Take Shape
These blueprints paint a vivid picture of the envisioned dashboard, bringing its core components to life:
1. Forecast Extension in Focus:
Prominent horizontal bar charts prominently display forecast extensions, providing an intuitive visual representation of future trends and projections.
2. KPI Modules at a Glance:
Key performance indicators (KPIs) are displayed in dedicated modules, each featuring clear and concise visualizations that make it effortless for users to grasp essential metrics.
3. Comprehensive Inventory and Purchase Overview:
A well-structured list view seamlessly integrates inventory and purchase information, allowing users to effortlessly scan and analyze critical data points.
Testing the Vision:
These wireframes serve as a robust foundation for rigorous testing scenarios, gathering valuable feedback to refine the dashboard's design and functionality.
Filtering
When a user creates a filter combination it needs to automate the results... in this case fill in the gaps!
This example (Filter Combo 2) 'Well deepening' and 'Actively exploring' are selected and the 'Measurement' is 'Producing'.
In this event the user did not select 'drilling clockwise data' which is needed to create the 'Measurement' of 'Producing'. Production data is dependent on several factors, hope this part makes sense!
The drilling clockwise data would need to be added into that filter combination without the user input, which is a automation scenario.
Steps to being active
This shows the 'drilling clockwise data' as a 3 phase approach for drilling to become monitored as active rig.
Phase 1 - Setup: Refers to mechanical attachments and location.
Phase 2 - Completion: Refers to the angle of the drill and depth. (e.g. the angle of drill could mean an existing well is being repurposed ).
Phase 3 - Activity: If the drill is going clockwise that data means the drill is going into the ground and active.
Modeling Geophysical Dynamics
We incorporated maps and satellite data to map soil types, contaminant hotspots, and other relevant environmental factors.
Enhanced Risk Assessment: Identify potential environmental hazards and their impact on drilling operations, mitigating risks and optimizing resource allocation.
Improved Optimization Strategies: Predict long-term production trends and equipment performance, enabling optimization of drilling schedules, maintenance routines, and resource allocation.
Scenario Planning and Preparedness: Explore various "what-if" scenarios under different environmental and operational conditions, facilitating informed decision-making and proactive risk management.
Benefits for Estimation and Purchasing
Informed Forecasting: Visualizing density and distribution patterns aids in accurate demand estimation, leading to optimized inventory levels and reduced stock-out risks.
Strategic Purchasing Decisions: Identifying regional trends and activity levels supports strategic purchasing choices, maximizing efficiency and cost-effectiveness.
Enhanced Collaboration and Communication: The shared visual map facilitates seamless collaboration and communication across teams, fostering data-driven decision-making.
Next Steps:
Rigorous User Testing: Gather feedback from diverse stakeholders to refine the map's design, functionality, and overall user experience.
Explore Additional Data Layers: Consider incorporating additional data layers, such as traffic patterns, customer demographics, or competitor locations, to enrich insights and uncover hidden opportunities.
Integrate with Other Systems: Seamlessly connect the map view with other business intelligence tools and dashboards, enabling comprehensive data analysis and holistic decision-making.
By harnessing the power of Google Maps API and thoughtful design choices, this map view holds immense potential to visualize crucial business data.