FINANCE

Democratizing insights & data

Data insights model comprised of company key performance indicators for sales operations

Results

We successfully surfaced actionable sales KPI’s and funneled them to the client’s business intelligence tool of choice. We met the sales operations goals of high visibility and easy manipulation by leadership, not just the few IT data experts.

Less confusion, less time wasted

Now, a simple tool is available to dynamically analyze company KPIs. This prevented meetings, email chains, and wait times for new reports in response to follow-up questions.

Confidence in numbers

By making it easier to verify answers and move to the next question, leaders can get helpful data insights from a data visualization tool.

Benefits in weeks, not months

The client avoided starting with a lengthy data science initiative with machine learning algorithms. They benefitted from immediate value by making sequestered transaction data accessible to key personnel.

Value focused = lower cost

By lowering initial complexity, our tool got to the heart of the problem at a reasonable price, even if some big buzzwords didn’t make it in.

Background

Interpretation of transactional data from a CRM system can take days out of the month, relying on one-off reports that lead to more questions and follow-up meetings. A mid-sized financial institution asked us to help create a flexible data analytics solution to improve leadership’s ability to monitor the business and make the right decisions.

Team

Project/product mgmt.
Cloud Architecture
Data Architecture
Development
QA

Build type

Hybrid & Greenfield

Tech stack

Python
AWS
PostgreSQL
Data Visualization Tool

What we did

Simplified Insights Model

We started with our end user, the executive with strategic and tactical questions about sales performance. After quick interviews and research around key CRM data, we designed a structure for critical success metrics to inform our Insights Model.

Lean and clear Insights Model
Easy to view KPI’s
Quick stakeholder feedback from real, iterative prototypes

Lightweight cloud architecture

We focused on creating an Insights Model that was easy to stand up, maintain, continuously improve, and hand over to the client with little/no maintenance or tech support.

A straightforward, serverless function working in conjunction with a relational cloud database
Easy client transfer, standalone AWS account
Time-saving, flexible AWS architecture ready for iterative feedback from client demos and other learnings, instead of inefficient boilerplate code

Future-proofing

To ensure scalability and long-term value, the insights model enables the addition of data insights from HR, ERP, finance/accounting, and other pillar systems in the future.