“Strategy” is the plan of action designed to achieve an overall or long-term goal. Unlocking the true potential of an organization’s data becomes a challenge when there are no goals defined. A data-focused strategy can help in overcoming these challenges.
Not All Data is Created Equal
Organizations capture their sales data, customer data, and other data available and, depending on the technology capabilities they have, create data stores in the form of data warehouses, data lakes, and big data systems. However, it is crucial to understand that every data point we capture should serve the purpose of achieving a specific business outcome. This means the data leveraged should be focused on decision making, operational efficiency, and the development of new business models.
Data Strategy vs. Business Strategy: What’s the Difference?
Before moving into best practices and techniques around a good data strategy, we should know how it is different from a business strategy.
A Data Strategy, Explained
A data strategy means leveraging insights to drive improvements by managing and exploiting data across business and mapping out a roadmap for defining how it is to be achieved. When a business is trying to create processes and identify how data can be used effectively for solving business problems going forward, this is considered a data strategy.
A Business Strategy, Explained
A business strategy can help in identifying the right priorities of the business and articulating the questions that need to be answered, whereas, a data strategy helps in identifying how you can leverage your existing data sources to answer those questions. It is important to understand that there is a synergistic relationship between a company’s business strategy and the data strategy. The latter should be driven by the former, not the other way around, or they should go hand in hand.
Every organization will have different methods to create a data strategy. However, the following are some of the principles that should be followed.
Create a Problem Statement
The first step is identifying what it is that you want to achieve as this drives every other aspect of the process. It involves understanding the business as a whole, identifying the pain points, communicating with the right stakeholders in play, and articulating the goals in a clear and understandable problem statement.
Compartmentalize the Data
Once we know the questions and the business problems, the next step becomes isolating the data that can help in answering the questions. An organization trying to improve its customer retention will benefit from putting its energy in analyzing the customer data instead of going through and analyzing the whole data store to identify any patterns. The right questions supported by the right data will help you get a 360-degree view of the customer and in turn, will help the business make the right decisions about the customers.
Leverage the Right Tools and Technologies
But if the data cannot be turned into insights and even if it can be, failure to identify the right technical requirements is not going to help. Hence, getting into the details of how the data will be analyzed, how insights will be presented, and what you would need to support it becomes the next step.
How Amazon Uses Customer Data to Improve Outcomes
One of the best examples of utilizing customer data to improve business outcomes is Amazon. It leverages its vast data sources that contain customer profiles such as buying habits, preferences, and buying history, to provide the right product recommendations and improve customer service. This helped them to streamline their operations, make better decisions, and improve business performance.
The right data strategy cycle not only helps in identifying the most prominent use cases that can be solved using the data for an organization but also helps in prioritizing the ones which can be achieved in a shorter amount of time.
How Can a Data Strategy Help My Organization?
Making the right business decisions sets your organization up for success. In the current scenario, the organizations which produce large amounts of data are good, but the better organizations know how to use it for making informed decisions.
A data strategy can help identify the problem you want to solve and create an end to end roadmap to pave the way for a data-driven organizational culture.
Here are some questions that can be answered during the process:
- How will the data be stored?
- How will the processes for transforming data be set up so that it can be analyzed and used across the organization?
- How will the appropriate provisioning rules be structured – to share only what is required and keeping it secure?
- How will the business define common data standards across the organization to maintain consistency?
- How do we identify the right technology that allows systems to interact and use the data, eliminating the need for separate implementations?
A good data strategy will not only help you identify the right questions and the data to capture but will help define the right roadmap to achieve the long-term goals of your business. It will also help build the business case to implement a data-driven culture by outlining the benefits, a realistic timeframe, and the costs associated with the implementation.
Get More Results with a Data Strategy
The power of your data is not in what you capture. Rather, it lies in the questions that you want to answer and how you are going to leverage it to improve your business. Collecting and analyzing all the data that you can get your hands on will not help if you don’t know what insights you want to look at, what business process you want to improve, the decisions that you want to take, and how it will be used across the organization.
Ready to make a change? Contact us to discuss your data strategy needs.
