The Council of Forest Industries partnered with FreshBI to streamline its data processes, eliminate reporting delays and deliver on-demand insights to members with confidence. FreshBI started from the members’ needs, gave COFI’s data one consistent structure, and built a pipeline that is ready for AI.
The BC Council of Forest Industries (COFI) represents the majority of lumber, pulp and paper, and manufactured wood producers across British Columbia. As an industry-leading organization, COFI plays a critical role in advocating for the interests of its members and collaborating with government, First Nations, communities, labor and other stakeholders. Its goal is to foster a healthy, diversified and sustainable forest industry that benefits people and families across BC.
A core part of COFI’s value proposition lies in analyzing and delivering comprehensive insights on lumber harvesting and pricing. To keep its leadership position and better serve members, COFI recognized the need to modernize how it delivers those insights.
Every week, COFI’s team faced the same challenge: hours spent compiling spreadsheets, checking formulas and rushing to meet reporting deadlines. As membership grew and demand for up-to-date forestry data increased, the old system couldn’t keep up.
Compiling spreadsheets, checking formulas and racing deadlines consumed hours of the team’s week, every week.
Members increasingly demanded timely, accurate data on forest product exports, lumber harvesting activity and market pricing, accessible in real time.
Manual, labor-intensive processes limited both COFI’s efficiency and its ability to deliver insight at the pace stakeholders required.
COFI was committed to delivering timely, accurate insights to members across British Columbia’s forest industry, and needed tools that matched that commitment.
FreshBI began with an assessment of how COFI handled its data and what members needed. Then the data got one consistent structure, so every dashboard reads the same numbers, every time.
Python scripts pull data from a national lumber statistics API on a schedule, replacing hand-assembled spreadsheets.
Automated cleansing and structuring turns raw data into a consistent, analysis-ready shape that every report shares.
A SQL database provides secure, scalable storage, so there is a single home for the data instead of many spreadsheet copies.
The solution combined Python automation, SQL databases and Power BI dashboards. It solves today’s reporting problem, and it lays the groundwork for AI integration.
Data is extracted from a national lumber statistics API with Python, then cleansed and structured automatically, so the team no longer assembles the weekly picture by hand.
A SQL database holds the structured data consistently and securely, giving COFI a dependable foundation for every dashboard it publishes.
Interactive Power BI dashboards are tailored to COFI’s unique data and to forest-industry professionals, with filters and exportable tables so members can get the data they need on their own.
The entire pipeline, from raw data to client-facing insight, was designed to be efficient, scalable and tailored to industry-specific requirements.
Initial assessment of COFI’s existing data handling practices and member needs.
Python scripts automate data extraction, cleansing and structuring.
Integration into a SQL database for consistent and secure storage.
Dashboard design in Power BI, tailored to forest industry professionals.
Exportable tables and filters deployed to ensure usability and client independence.
The partnership empowered COFI to better meet the expectations of its members and positioned the organization as a tech-forward leader in forestry analytics.
The platform does more than fix today’s reporting. It was built so AI can be added later without rework.
Automated data pipelines can feed future large language models for narrative reporting or natural-language queries.
A structured, analysis-ready data layer suitable for training or integrating generative AI.
Dashboards that empower members today and provide a launchpad for predictive and conversational interfaces tomorrow.
Curious what AI readiness looks like for your own data? Start with AI-Ready Data or our data platform architecture approach.
By starting with an assessment of how COFI handled its data and what members needed, then automating extraction and cleansing with Python, centralizing storage in a SQL database and building Power BI dashboards tailored to forest-industry users, with filters and exportable tables so members can self-serve.
It is data that has already been extracted, cleansed and structured, so analysts, and later AI models, can use it directly. COFI’s pipeline produces that layer, which means narrative reporting or natural-language queries can be added later without rework. See our data platform architecture approach.
Yes. At COFI, the weekly spreadsheet cycle was automated end to end with a Python-to-SQL-to-Power-BI pipeline. FreshBI typically delivers a first production solution in as little as three weeks. See pricing.
We’ll show you which of your recurring reports can be automated, and what an AI-ready data foundation would make possible next.
