4 Steps to Becoming a Data-Driven Organization

Data is the lifeblood of almost every modern organization today. With so much data available, organizations that make better use of that data are able to achieve greater success.

Guest post by Bash Sarmiento

Photo by Mikael Blomkvist from Pexels

This is especially true when it comes to the way decisions are made in an organization, because better informed choices can lead to more successful outcomes with increased efficiency and productivity for all involved.

A lot of business organizations make significant choices about long-term plans, operational activities, and short-term efforts based on incomplete data. Making decisions in this manner can often lead to a slower, more difficult path towards success.

Incorporating a data-driven approach into your company’s decision-making process identifies effective solutions in a much shorter timeframe. By basing decisions on verifiable data rather than incomplete or inaccurate information, organization are put in a better position to make informed choices that have a better chance of panning out. This, in turn, leads to increased efficiency as well as overall success for your organization.

So how do you go about making your business data-driven?

In this article, we go over the four things you need to consider in setting up a data-driven approach for your organization.

Deciding on your data sources

The first step in setting up a data-driven approach is to identify your internal and external data sources.

External sources are typically public information that is accessible without any special effort, such as demographic or economic indicators published by government agencies. Internal sources, on the other hand, consist of data that is generated within your company’s systems and is not typically available to the public. Examples of internal data sources include customer purchase history, call center logs, or email open rates.

You can also look into advanced internal sources, like logs from web and mobile applications. These sources provide a detailed view into the customer’s behavior, including what they are doing on your site or app as well as how engaged they are with different features.

Once you have identified the available data sources for your organization, you can begin to determine which ones will be most useful for informing your decision-making process.

Data handling and storage

After the data is collected, it needs to be properly handled and stored.

Managing data troves requires you to choose the best data storage method for your organization:

A data lake is a large collection of unstructured raw data that may be accessed and updated quickly. They serve as a repository for data that has not yet been assigned to a specific purpose. A data warehouse is a data management system that is used to help companies extract insights from their data. Business intelligence (BI) activities, particularly analytics, are aided by this type of data management system. Data warehouses frequently contain vast amounts of historical data for queries and analysis. A data mart contains cleaned, aggregated data only on specific domains like marketing, sales, or finance.

Most organizations will require a combination of all three models. However, the specific storage system you choose will be based on the needs of your organization.

Once you have selected a data storage model, it is important to develop a plan for managing and governing the data so that it can be effectively used. This includes setting up processes and protocols for adding new data as well as removing or modifying existing information.

A dedicated analytics team

To get the most out of big data, you will need to have a dedicated team that is responsible for making sense of the information.

Without their expertise in setting up extensive databases and using analytics tools, your organization’s ability to use its collected data effectively will be limited.

Having this type of talent on hand can help organizations get more out of their existing data, allowing them to make smarter decisions.

They can also help you test your new data tools through public beta testing before you fully implement them.

This team will also be at the forefront of your data privacy policies. Data-driven organizations must contend with a host of data privacy laws and regulations, which can vary from country to country.

Data analytics and AI

Once your organization has identified its internal and external sources, properly handled and stored the data, you can begin using it for making more informed decisions with advanced analytics.

Data analytics help you to glean insights from your available data and apply those learnings directly to specific business problems. AI processes are also expedited once you have your organization’s data analytics program is set up.

Together, these two tools can help you make better decisions faster and more efficiently.

A few of the benefits these tools bring to the table are:

  • More precise segmentation- Once you have a good understanding of your customer’s behavior, you can better target them with specific offers and products.
  • Improved value propositions- You will be better able to identify what your customers want and need from you. This can help improve retention rates for existing clients by offering them a more tailored solution.
  • More precise targeting- With the right data, you should also have an easier time knowing where best to invest your marketing efforts in order to get new business leads.
  • Improved pricing- Your ability to better tailor your pricing and value propositions can mean improved price sensitivity and

While the perks of data analytics are numerous, this process can be a financial and organizational drain. The bright side: industry experts believe that the benefits of data analytics and AI are soon to be within reach of smaller organizations. One key reason for this belief is the cost reductions of cloud GPU services in the future.

To become a data-driven organization, every step we outlined above must be incorporated. By focusing on one or two of these steps and neglecting the others, companies will not see desired results in their efforts. The only way for any company to expect a hefty ROI from pivoting to a data-driven approach is by looking at all parts of this process holistically. It might not be a quick magic solution, but it can be very powerful when done right.


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