At Company Watch, we empower organisations to make confident, data-driven decisions by providing clarity in financial risk. One such success story comes from Alvarez & Marsal (A&M), where Company Watch has played a key role in transforming how financial data is ingested, analysed, and shared across the business development function.
Client
Alvarez & Marsal (A&M) is a global professional services firm known for driving operational improvement and delivering measurable results. Within their UK operations, the business development team relies on large, complex datasets to generate market insights.
With a focus on efficiency and scalability, A&M has continuously sought ways to improve their data workflows, especially where manual processes were creating bottlenecks.
Challenge
Each month, A&M ingests a substantial dataset made up of UK companies, filtered according to a wide range of financial and structural criteria. The data ultimately flows into a Power BI environment, where it informs key decisions and is accessed by a wider group of business users.
However, the previous process for acquiring and loading this data was heavily reliant on manual steps. The data was initially shared via encrypted links, then downloaded and manually ingested on the client side. While this process worked, it lacked efficiency and posed risks related to timeliness, data integrity, and scalability.
“There was a real appetite within the business to reduce manual touchpoints and automate as many processes as possible. The existing method of data exchange, although functional, simply didn’t align with our vision for a more agile, data-driven operation.”
Alvarez & Marsal (A&M)
Solution
Company Watch, a certified Google Cloud Platform partner, stepped in to deliver a streamlined, automated solution using Google BigQuery. By creating a dedicated BigQuery instance tailored to A&M’s data needs, Company Watch was able to provide secure, direct access to all relevant datasets, including:
- Financial performance metrics
- Company Watch scores
- Charge holder information
- Ownership and group structure data
Using a secure service account key, the A&M team can now retrieve the latest data programmatically in real time, completely eliminating the need for manual downloads or client-side processing.
This method of delivery effectively removes any manual intervention, enabling the data to flow from Company Watch’s data warehouse seamlessly and securely to the client’s Power BI environment. The end result is a fully integrated system that supports faster insights and improved operational efficiency.
Results
Since implementing the BigQuery integration, A&M has significantly improved its data ingestion process. Realtime updates that previously required multiple manual steps are now executed automatically, saving valuable time and reducing operational risk.
The seamless delivery pipeline ensures that business users always have access to the most current data, empowering deeper analysis and smarter targeting within the business development function.
By leveraging this new architecture, A&M has taken a decisive step toward becoming a more agile, data-driven organisation.
A trusted strategic partner
Company Watch’s role in transforming A&M’s data pipeline underscores its position as a trusted partner in financial insight delivery. What started as a need for automation has evolved into a deeper collaboration focused on strategic enablement and long-term data excellence.
As A&M continues to scale and refine its data operations, Company Watch remains committed to delivering innovative solutions that unlock greater value from financial information.
“Company Watch has been a game-changer for our data operations. Their expertise in automating and streamlining our data ingestion process has not only saved us significant time but also enhanced the accuracy and reliability of our insights. The seamless integration with Google BigQuery has empowered our team to focus on strategic decision-making, knowing that we have access to the most current and comprehensive data at our fingertips. This collaboration has truly elevated our ability to drive data-driven growth and operational excellence.”
Alvarez & Marsal (A&M)
