Tableau Case Studies ThoughtStorm and Tableau – Effectively Engaging The Data

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	ThoughtStorm and Tableau – Effectively Engaging The Data Tableau

ThoughtStorm and Tableau – Effectively Engaging The Data

Tableau

Technology Category	Analytics & Modeling - Data-as-a-Service
Applicable Industries	Finance & Insurance Retail
Applicable Functions	Business Operation
Services	Data Science Services
Challenge	ThoughtStorm, an investment portfolio company, was struggling with evaluating large amounts of data to come up with business strategies. They had a team of SQL programmers, analysts, and statistical experts, but the process was slow and inefficient. The analysts often didn't understand the strategic and management considerations of the financial experts, and the financial experts didn't have time to run complex statistical software. This was causing ThoughtStorm to lose time and ground, which was unacceptable to the company's co-founder and managing director, Mike Princi. Read More
About Customer	ThoughtStorm is an investment portfolio company that provides a variety of services, including financial advisory services, interim management services, and strategic planning services. Their clients range from Charles Schwab to Google, and they all have a common need: to evaluate large amounts of data in order to come up with business strategies faster, easier, and more effectively. ThoughtStorm's co-founder and managing director, Mike Princi, is a former infantry ground officer, and he is committed to ensuring that the company does not lose ground in its operations. Read More
Solution	ThoughtStorm turned to Tableau to increase the speed and effectiveness of their analytical capabilities. They used Tableau to track key performance areas such as gross margins, number of orders, and total revenue. They were able to quickly identify trends and ask the right questions to understand why certain trends were occurring. For example, they noticed that the business was doing much better in the previous year during the same time period, and they were able to isolate one important factor: they didn't have the magnitude of the back order and fill rate issues that they currently had. With this insight, they were able to take immediate action to start pushing volume into the business and lay out plans to increase revenue per order. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Data-as-a-Service

Applicable Industries

Finance & Insurance

Retail

Applicable Functions

Business Operation

Services

Data Science Services

Challenge

ThoughtStorm, an investment portfolio company, was struggling with evaluating large amounts of data to come up with business strategies. They had a team of SQL programmers, analysts, and statistical experts, but the process was slow and inefficient. The analysts often didn't understand the strategic and management considerations of the financial experts, and the financial experts didn't have time to run complex statistical software. This was causing ThoughtStorm to lose time and ground, which was unacceptable to the company's co-founder and managing director, Mike Princi.

About Customer

ThoughtStorm is an investment portfolio company that provides a variety of services, including financial advisory services, interim management services, and strategic planning services. Their clients range from Charles Schwab to Google, and they all have a common need: to evaluate large amounts of data in order to come up with business strategies faster, easier, and more effectively. ThoughtStorm's co-founder and managing director, Mike Princi, is a former infantry ground officer, and he is committed to ensuring that the company does not lose ground in its operations.

Solution

ThoughtStorm turned to Tableau to increase the speed and effectiveness of their analytical capabilities. They used Tableau to track key performance areas such as gross margins, number of orders, and total revenue. They were able to quickly identify trends and ask the right questions to understand why certain trends were occurring. For example, they noticed that the business was doing much better in the previous year during the same time period, and they were able to isolate one important factor: they didn't have the magnitude of the back order and fill rate issues that they currently had. With this insight, they were able to take immediate action to start pushing volume into the business and lay out plans to increase revenue per order.

Impact #1	ThoughtStorm was able to understand what was happening in the business.
Impact #2	They were able to create a set of plans that were related to how the business operated from the bottom up.
Impact #3	They were able to implement a quick set of management policies that allowed them to implement a model that gave them very strong insights about the business and the performance of their business.

Impact #1

ThoughtStorm was able to understand what was happening in the business.

Impact #2

They were able to create a set of plans that were related to how the business operated from the bottom up.

Impact #3

They were able to implement a quick set of management policies that allowed them to implement a model that gave them very strong insights about the business and the performance of their business.

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Overview

ThoughtStorm and Tableau – Effectively Engaging The Data

Operational Impact