Are You a Data-Driven Organization?

by Data and Analytics Team on December 22, 2020
Precision Blog

Are you a data driven organization? The truth is, data and analytics are nothing new. Many organizations talk about becoming data-driven, but very few know what the concept really means and how to achieve it. A strong and data-driven culture remains obscure, and data is rarely the universal basis for companies decision making. It’s time to change that. In this blog, find the reasons and steps to become a data-driven organization.

What Does it Mean to be a Data-Driven Organization?
Being a data-driven organization means you are a business that is dominating your sector as well as creates new markets by generating actionable insights through data collection and analytics. Forrester Research has identified a statistic that shows that data-driven businesses are growing at an average of more than 30% annually and are on track to earn $1.8 trillion by 2021.

So, what does it mean to be a data-driven organization? The answer relies on many factors. A data-driven company must embed a data culture. Treating data as a resource only relevant to specific parts of your organization for reports and strategic planning limits the potential for developing insights. These insights are able to feed into innovation and new product development. Data must be in the company culture and made available to everyone in order to make better decisions and improvements. This makes data literacy and access to data and analytics tools for everyone in the organization very important.

The Steps to Becoming a Data-Driven Organization
Becoming a data-driven organization is an opportunity for teams to lead strategically as well as offer guidance and leadership. The Harvard Business Review provides great insights on how to shift your company’s mindset and culture with data at it’s core. Listed below are the steps to creating a data-driven environment.

1. Data-driven culture starts at the very top.
A company with a strong data-driven culture has top managers who set an expectation that decisions must be anchored in data. It’s very important to promote evidence-based actions. With a company-wide use of data and analytics, employees are able to communicate with senior leaders and managers with supporting facts.

2. Choose metrics with care – and cunning.
Creating detailed metrics on your company or customers allows for a quantitative analysis of the impact of that data. IT leaders are able to choose what measure and metrics they expect employees to use.

3. Don’t pigeonhole your data scientists.
Typically, data scientists are isolated within in a company, which leads to them and the business leaders knowing very little about each other. It’s important to remember that data and analytics won’t survive or provide value if it operates separately from the business. Boundaries between the business and data scientists should be obsolete. By bringing data science closer to your business, you are also bringing the business closer to data science. This encourages employees to become more educated in data and analytics.

4. Fix basic data-access issues quickly.
It’s impossible for your organization to become data-driven if employees have difficulty obtaining data. Role based access to data and analytics should be granted to all of your employees. If your employees and analysts are starved of information, they won’t be able to give proper analysis to your company or customers. There should also be an enterprise data view created for 360 visibility of data.

5. Quantify uncertainty.
As we all know, absolute certainty is impossible. Being quantitative about levels of uncertainty has three effects. First, it forces decision makers to face potential sources of uncertainty. For example, is the data reliable? Second, analysts gain a deeper understanding of their models when they have to evaluate uncertainty. Third, emphasis on understanding uncertainty pushes companies to run experiments. For instance, creating controlled trials of ideas before making decisions.

6. Make proofs of concept simple and robust
Promising ideas greatly out numbers practical ones. It’s not until organizations put proofs of concept in production that the difference becomes clear. You are also able to engineer proofs of concept where a core part of the concept is its viability in production.

7. Specialized training should be offered just in time.
Many skills should be taught when educating and training employees about data. Not only should they be trained in basic skills like coding, but there should also be a focus on specialized analytical concepts and tooling just before they are needed.

8. Use analytics to help employees, not just customers.
Enabling employees to obtain data themselves allows them to learn new skills and better handle data. This benefits employees by saving time, avoiding rework, and avoiding getting frequently needed information.

9. Be willing to trade flexibility for consistency – at least in the short term.
Many companies that depend on data have different “data tribes”. Each may have its own preferred sources of information, metrics, and programming languages. Having this many “data tribes” and inconsistencies can be a disaster. For success, organizations should pick undisputed metrics and programming languages so that they entire company is on the same page.

10. Get in the habit of explaining analytical choices.
For many analytical problems, there are multiple correct approaches. It’s a good idea to ask teams how they approached a problem, what alternatives they considered, what they understood the tradeoffs to be, and why they chose that approach over others. This allows for a deeper understanding of the approaches and often prompts teams to consider alternatives or other fundamental assumptions.

Becoming a data-driven organization offers many positive attributes. As data becomes more relevant and important in business, your company should consider taking active measures to data-driven. If you have any questions about data and analytics, please contact us.



About Precision
Precision Technologies Corp. (PTC) is a leading full stack IT Company with a diversified portfolio of agile transformation, application & mobile development, the PMO suite, automation, analytics, salesforce solutions and technology staffing services. Since 2010, our clients have leveraged our staffing and consulting experience to obtain escalated technical services across the industries. We often are told that our solutions are very precise, cost-effective and process driven, thereby delivering intended results.