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6 Stages on the Journey to Becoming Data-Driven

Rafael M. Dourado

Being data-driven is about more than just having information on hand. Learn how to begin (or reinitiate) your company’s journey to becoming data-driven.
Young tourist checking a map as she travels through New York

Where do we have inefficiencies in our workflows? What kinds of products do our customers need most? These are the types of questions you and other leaders in your company probably want to answer with clear, high-quality data.

Previous generations of leaders had to worry about not having enough information to find answers. Now, executives like you must combat the opposite problem: Having an overwhelming amount of data to sort through to make smart decisions.  

At Programmers, we understand that being data-driven is about more than just having some information on hand. That’s why we view being data-driven as a journey with different action items along the way, from leveraging new digital capabilities to adopting a more data-oriented mindset throughout your organization. 

Below, discover what characterizes each step of the journey, identify where you stand today, and find your next steps to unlocking next-level insights. Plus, you’ll learn how Programmers’ data analytics solutions can help you along the way.

Elevator heading to the 6th floor

The Six Stages 

Before you can begin improving your organization’s data capabilities, it’s important to know where you’re starting. Identify which of the six stages below best represents how your company currently collects, organizes, distributes, and leverages data.

1) Impromptu Data Use

Companies in this stage rarely collect data or store it for analytics. Even when they do gather information, it is often done manually, leading to low-quality data that is unreliable for decision-making.  

Next steps: Identify what data will most benefit your organization and consider the most reliable sources for that information. Then, work with a consulting company like Programmers to understand how your organization can ingest, clean, store, and make reports out of this data. 

2) Fragmented

Organizations collect more data here than in the impromptu stage. However, each business unit works mostly with its own data source and does not share all the information they have with other departments. This creates data silos, which make it difficult to facilitate company-wide decisions and lead to misunderstandings between teams. 

Next steps: Build a centralized data repository that can be the single source of truth for your company. Ensure it is structured in a way that best suits your organization’s needs, whether it be a data warehouse, lake, or lakehouse. 

Young male and female workers checking data in office with laptops and monitor screens

3) Normalized 

At this stage, companies have a secure and reliable data repository. This repository has well-defined management, governance, and a basic system of reporting. Employees can generally access the data they need.  

Next steps: Expand employees’ ability to create reports from this data and track KPIs. Programmers’ REACT service helps by putting together mission-critical reports for your organization through Power BI and training your staff on how to best leverage self-service analytics.

4) Managed

Going beyond basic reporting, companies at the managed stage have more comprehensive self-service and governance structures. This encourages users to explore data in-depth even if they have little or no background in data science. At this point, the company is beginning to realize the positive effects of decision-making backed by reliable information.  

Next steps: Use AI to begin implementing predictive and prescriptive analytics. Programmers’ INSIGHTS service can help you get started utilizing Microsoft Azure for these next-level capabilities.  

5) Advanced

Characterizing this stage is a robust data science infrastructure. Organizations can not only access reports but also quickly deploy new data products that respond to emerging business needs. Beyond the technology, these companies have also taken the time to foster a data-curious culture in their organization with strong buy-in at all levels. 

Next steps: Ensure you’re getting the most up-to-date information possible by tracking data in real-time. Here’s an example: We helped our client in logistics use real-time data to improve fleet visibility, driver safety, and on-time shipments. 

Truck driving in the desert, illustrating the data-driven journey case study

6) Data-Driven 

Making information-based decisions is deeply rooted in your company culture and business processes at this stage. Each stakeholder can seamlessly create reports with real-time data to gain key insights. 

Also, your organization now has the ability to anticipate emerging customer needs and target internal inefficiencies. Data in the organization is democratized, integrated, and fully governed. 

Considering the Human Element 

Like most aspects of your business, becoming data-driven will require more than just advanced digital capabilities. You’ll also need the coordinated effort of teams throughout your organization.

Make sure that your data strategy helps each department find the information they need faster and strengthens their professional development. Then, sit down with the leaders of each department and discuss how this custom-tailored approach benefits them. 

As you begin removing data silos within your organization, ensure that culture silos also become a thing of the past. With a centralized data repository, there should be nothing stopping departments from coming together to make decisions and establish best practices. Make sure they have plenty of opportunities for this collaboration. 

Two white professionals, one male and the other female, placing notes on wall outlining data goals

Accelerate Your Company’s Journey to Becoming Data-Driven

With so many factors to keep in mind, embarking on a journey to become data-driven may seem intimidating at first. Luckily, Programmers has developed a full slate of services to make your path exponentially easier and less time-intensive. 

Here’s what we offer: 

  • Data Platform Maturity Assessment, allowing you to see where your capabilities stand today
  • Development of data repositories such as data lakes, warehouses, and lakehouses 
  • Programmers’ REACT, streamlining self-service analytics
  • Programmers’ INSIGHTS, unlocking predictive and prescriptive analytics with AI
  • Real-time analytics solutions
  • Building a data governance framework

Visit our data analytics solutions page to learn more. And, when you’re ready to begin leveraging our experts’ insights, fill out our contact form. 

Let us know how we can help you.

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