When we take a trip and want to save time and resources, we must be clear about where we want to go and how we will do it.
Something similar happens in the business world, where our business objectives tell us where to go. The data strategy is a powerful tool to accelerate our path toward the goal.
When we talk about data strategy, we refer to a long-term plan in which, based on our business objectives, we define the technology, people, and methods that will help our organization grows, driven by the power of data analysis.
In addition to a clear vision, the data strategy must have quantifiable objectives prioritizing actions to measure their effectiveness.
What benefits does a good data strategy bring?
The data strategy gives us a framework that determines how we will collect and organize the information available to our company. It also determines how we will analyze that data and our decisions based on them.
Accordingly, any decision arising from our data strategy must be aligned with the business objectives and strategy. If we achieve this, we can expect the following benefits:
Significant improvements in the user experience
Data analytics and strategy allow us to accurately understand the needs of our audience, anticipate trends, and deliver what they need when they need it and exactly how they need it.
Additionally, companies can use their data strategy to detect points where they can improve their value proposition by making intelligent adjustments representing a significant return on investment.
Increased operational effectiveness throughout the organization
A well-designed data strategy can democratize data use so that no part of the business is left without a significant boost from data analysis.
This can be achieved in several ways that depend a lot on the specific needs of each company. For example, the professionals in charge of data analysis may work in a centralized team, be distributed in different areas of the organization, or have mixed participation with some centralized functions. Whatever the case, people driving the data strategy must work to create a culture in which any area of the company can benefit from the data strategy while avoiding working in independent silos.
Accurate and unified knowledge of each part of the business
Today, most companies interact with their users through multiple channels. We are talking about physical stores, websites, and apps, among other options that improve and diversify the experience but sometimes make it difficult to have a unified view of the user.
This is one of the common problems that can be overcome relatively easily by implementing a robust data strategy.
Through architecture and data management, we can centralize the data collected in different channels and guarantee that, regardless of their source, they are reliable as part of a coherent whole that facilitates decision-making.
Automation of manual processesAutomation is a fundamental tool to drive the work of an analytics team. When insight creation is automated through tools such as artificial intelligence, the organization gains actionable insights in a continuous and timely manner.
In addition, automation frees up time and resources in the analytics teams, which allows them to focus their efforts on strengthening strategic aspects to ensure the success of the data strategy.
Timely reactions to changes and opportunities
In addition to ensuring that each data source is centralized and collaboratively works with other sources, a considerable advantage of having a data strategy is that our data can be analyzed and viewed without long waiting periods.
This means greater operational effectiveness and sometimes the opportunity to detect and anticipate changes that can improve business opportunities.
Diversify your sources of income
Besides customizing existing products and services, data analytics and strategy allow companies to detect new opportunities to develop products or even rely on precise and reliable information to evolve their business model.
Implementing a data strategy allows companies to evolve safely by providing data-driven answers to tough questions such as: Where should our business model go next? Or what aspects of our work need to be strengthened to survive in an ever-changing environment?
How to create a data strategy in five steps
As we have already said, business objectives should determine the goals of our data and analytics strategy. Once we are clear about those objectives, we can create a solid plan by following these steps:
Determine the impact that your strategy should have on business goals.
Prioritize the actions that must be performed first to meet the objectives.
Build the projects, programs, and products necessary to implement the strategy.
Quickly implement the projects, programs, and products created in step 3.
Disseminate the strategy. The entire organization must understand the impact and importance of the data and analytics strategy; in this way, it will be strengthened with essential insights to enhance its effects.
What elements are essential to create a data strategy?
Here are four elements that you must integrate and make work together to build a good data strategy:
Expert IT talentRegardless of the size of your organization, it is crucial to have the professionals to take advantage of the data and achieve your goals.
Today, many companies have a group of professionals in charge of making the objectives of the data strategy a reality. This group, which includes different profiles that include analysts, engineers, and data scientists, must be able to create solutions and ensure data quality and availability.
As we said before, these experts can be centralized in what is known as a defensive data strategy or, on the contrary, distributed in different areas of the organization, which is an offensive strategy.
There are also mixed distributions, but whatever the type of strategy, the data team must offer agile and proactive work that constantly improves and allows innovation.
Technology and architectureFor a strategy to be able to deliver its full potential, it must be driven by the necessary technological tools. Here, cloud services, computing capacity, and virtually unlimited storage play a crucial role.
Moreover, when discussing architecture, we refer to the design that allows all the technological tools we use to implement our strategy to work coherently and collaboratively.
Choosing the right technology and defining a good architecture allows us to create solutions that answer vital questions such as: How will the information be organized? How are we going to view the data? What cutting-edge tools, such as Artificial Intelligence, can we employ for data analysis?
To put it in experts’ words: Regardless of whether the data comes from a physical store, a mobile app, a call center, or a web page, everyone must speak the same “language.”
Data governance involves defining how information is collected under legal parameters and the company’s needs. However, your most important responsibility is perhaps to safeguard the data with the highest security standards while ensuring they have a standardized quality regardless of origin.
This offers a unified vision of the business and the customer but, above all, ensures that the company has confidence in the data, making it an effective tool to achieve the objectives set.
We will not tire of repeating it: Business vision is the starting point for any successful data strategy.
Suppose we have a clear understanding of the company’s business priorities. In that case, we can build a data strategy focused on the continuous delivery of value in which each effort helps the company be closer to achieving its goals.
At this point, it is also essential to define the benefits expected from the data strategy and make the necessary measurements to objectively know the benefits of implementing it.
Are you seeking an ally to help you boost your data strategy and analytics?
At Pragma, we have years of experience working with companies at various levels of analytics maturity, and our teams of data professionals are ready to get down to business.
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