Introduction

A data-driven Organization will use the data as critical evidence to help inform and influence strategy. To be data-driven means cultivating a mindset throughout the business to continually use data and analytics to make fact-based business decisions. Becoming a data-driven organization is no longer a choice, but a necessity. Making decisions based on data-driven approaches not only increases the accuracy of results but also provides consistency in how the results are interpreted and fed back into the business.

However, several challenges continue to hinder businesses from becoming data-driven. The average organization today collects more data than ever before, and the variety of data types that are stored, managed, and analyzed has increased exponentially. Added to this, data is also spread across different locations, databases, cloud, and so on. Finally, talent with different data skills are needed to ingest, transform, aggregate, model, analyze and create insights.

To become effective data-driven organization, businesses need to perform the following:

• Data Collection & Processing:

Data undoubtedly is a key ingredient. It can’t just be any data; it has to be the right data. the dataset has to be relevant to the question at hand. It also has to be timely, accurate, clean, unbiased and most importantly, it has to be accurate. 

• Data Access & Modeling:

Data must be accessible and queryable. Having accurate, timely, and relevant data is not sufficient for an organization to be data-driven. It must be properly modeled so that it can be joinable, queryable, and shareable. The data must be in a form that can be joined with other enterprise data when necessary. There must be a data-sharing culture within the organization so that data can be joined such as combining master data with transaction data. So, siloed data is always going to reduce the scope of what can be achieved. There must be appropriate tools to query and slice/dice the data and reporting/analysis requires filtering, grouping, and aggregating data to reduce the large amounts of raw data into a smaller high value data.

• Reporting:

Reporting is the process of organizing data into informational summaries in order to monitor how different areas of a business are performing. Reporting tells what happened in the past and also provides a baseline from which to observe changes and trends. It is fundamentally backward view of the world and not entirely sufficient for an organization to be data-driven.

• Analysis:

Transforming data assets into competitive insights that will drive business decisions and actions using people, processes, and technologies. Reporting says what happened but Analysis says why it happened. Reporting is descriptive but Analysis is Prescriptive.

Reporting	Analysis
Descriptive	Prescriptive
Backward-looking	Forward-looking
Raise questions	Answer questions
Data –> Information	Data + Information –> Insights
Reports, dashboards	Findings, predictions, recommendations
What is happening	Why it is happening

courtesy: Dykes 2010 reporting vs analysis

DATA TEAM – WHO & WHAT

Where do they fit

Conclusion

• The human component of a great data-driven organization is a great analytics organization. Who are those people, and how should they be organized is the key.
• Analytics is a team sport. A well-oiled, data-driven organization is going to have both a range of analytical personnel with different roles and also with complementary skills.
• Skills & Qualities of Data Team: Numerate, detail-oriented and methodical, appropriately skeptical, data curious & lovers, good story tellers, and patient