Tecknoworks

The Problem

Complex, unpredictable supply chain touches wasting time and resources

The company struggled to efficiently manage the numerous, often unpredictable elements of their supply chain. Factors included weather, fuel costs, road tolls, warehousing taxes, international shipping logistics, traffic, exchange rates, and vendor pricing.

Because of these multiple and rapidly-changing factors, much of the supply chain management process involved last-minute adjustments that increased costs and assembly time. In addition, this largely manual approach was also taking up too much of the team members’ time and resources.

The Solution

Real-time data analysis and custom machine learning platform

We worked with the client to identify and track the key supply chain factors, using data the company already owned. Then, we created an algorithm that constantly analyzes these complex factors in real time. This allows the company to easily identify the most efficient and cost-effective routes.

For example, the algorithm might suggest shipping out small parts on a Wednesday instead of a Monday, rerouting a turbine tower through a less-expensive toll road, or warehousing a component for two extra days in order to transport it by train instead of a costly container ship.

In addition, the model continues to get smarter with each new project. After each completed assembly, the company compares the model forecast with the real data, and the algorithm adapts for more precise forecasting on each successive project.

The Results

Over $3M in savings within 18 months

As a result of their optimized supply chain, our client saves between $600,000 and $1,000,000 per project, resulting in over $3 million saved in just the first year and a half of implementation

The Problem
Enhancing sustainability efforts

The core challenge was to create a progressive app, suitable for mobile home screens and enriched with features lacking in the original platform, to boost user engagement and impact in combating carbon emissions. By buying these carbon offsets from the “Voluntary Carbon Market”, companies can measurably decrease the amount of CO2 equivalent they emit.

The Solution
Empowering carbon offsetting with an intuitive and engaging user interface

The newly created carbon offset app introduces a user-friendly interface for both individual and business users and helps users offset their carbon footprint & get rewarded for their sustainable actions.

It features three key elements for engagement and carbon offsetting: a list of carbon offset projects with details for informed choices, a carbon footprint calculator for environmental impact assessment, and a wallet for tracking transactions, subscriptions, and project support. Users can directly support carbon capture initiatives or choose projects based on their carbon footprint insights

The Problem
Delivering comprehensive data insights for mining industry cost and supply management

They wanted to provide their clients, worldwide companies in the mining industry, with detailed visibility into the global mining market for a data-driven view of:

● Historical and forecasted costs
● Supply and demand analysis
● Commodity availability
● Individual mine models

In addition, the client wanted to productize the datasets for subscription-based sales to the mining industry.

The Solution
Modernizing Data Management and Reporting with Scalable Cloud Solutions

We built a web platform used for data entry, validation, and central management, enabling quick adaptability to new data demands, complex calculations, and global coverage. We also improved the architecture and data streams, from archaic models to multi-user modern formats in the cloud. This improved data quality, reporting, and business workflows. The solution is now a standard offering generating profits, and it’s also used for specialized EU environmental consulting.

Technology Stack: C#, .NET Core, React JS, Microsoft SQL Server, Azure DevOps, Azure Cloud, SharePoint, Power BI, CI/CD

The Results

We achieved the client's goal of global coverage for all commodities

The project resulted in a significant increase in data quality, enabling over 50 people to simultaneously feed data into the system, enhancing the calculation model to include multiple complex variables, providing access to visualizations for the full nickel, steel, and aluminum value chains, and ensuring quick adaptability to new data demands.