Work

Selected Case Studies

Automation Strategy

Roadmap development and assessment for Financial Advisory Firm

A national financial advising company was evaluating whether to adopt a low-code platform as a strategic technology in their Digital Transformation efforts and needed platform expertise.

We were brought in to help evaluate the suitability of the platform for their needs. We met with stakeholders and created a feasibility study that showed how it could be leveraged effectively by this organization, developing a roadmap for implementation that highlighted gaps between effective usage of the platform and planned usage.

Based on discussions with leadership and the existing technology stack that this client already had in place, we helped pave the way to a decisive strategic decision.

Product Development

Professional Services Utilization Tool

A boutique professional services consulting company was in growth mode and needed a way to track and forecast team capacity utilization up to a year into the future. Existing spreadsheet based approaches were falling short.

We proposed a solution that leveraged the firm's existing productivity suite, combining their use of calendar events to track utilization with custom scripts to extract, transform and load their data into a central datasource for analysis. Finally, we built an interactive dashboard that charted projected utilization.

The custom solution was handed over successfully and placed into production use.

Data Design & Analytics

Data Integration PoC

A local catering company had an ambitious idea to leverage data from an online ordering platform to inform what and how much produce to buy each day, but didn't know how to approach the technical challenges involved.

We were engaged to evaluate the API of the platform and make recommendations on the feasibility of the plan. We built a working POC integrating their platform account data with the client's local datastore, which brought all order data into their workspace on a nightly basis. We then performed an analysis to determine how well that data would support their desire to predict food purchase quantities.

The proof of concept showed that their idea worked, and outlined the data cleansing and transformation that would need to be performed in order to support the desired outcome.