Data analytics: Foundations, strategy, projects
The only constant we have is change. Change happens so fast that it’s difficult to keep up. We need quicker and more reliable access to information if we want to stay ahead. We have to be smart about the ways we use our existing data and information, and how we incorporate data from wider sources as well.
From a leadership perspective, we need to think about the type of information that is required to drive our business. This is not only for operational reasons, but also for the strategic decisions we need to make to remain competitive, relevant, or develop a competitive advantage. In order to make effective business decisions, business managers and leaders will need to be able to ask the right questions.
These questions will be guided by the organization’s operational and strategic goals and objectives, but ultimately they rely on the timely availability of information and an indication of where the company is performing well, where it needs to improve, and opportunities for future growth and direction.
The thing about questions within data analytics is that the results of one question almost always leads to another. As each question reveals new information or insight, it leads us to question those results further. This is more than curiosity, it’s one of the ways in which organizations become data-led. It’s a voyage of discovery.
What does data-led mean?
Data-led organizations use data to predict and project possible outcomes, giving them a better ability to plan for the future. When an organization becomes data-led, it means that it makes strategic decisions based on data analytics and interpretation.
We live in a world where the volume of data grows every single day. All organizations, no matter their size or lifecycle stage, will need to become data-led to some degree. What varies is the starting point between different organizations. Factors such as organizational size, industry, maturity, and the extent to which data analytics is already used and embedded in the organization all play a part in determining that starting point.
Becoming data-led is more than asking questions and following the data. It’s a purposeful, intentional exercise that requires structure for the entire organization to follow the same principles and processes, all of which are informed by the organization’s data strategy.
What is a data strategy?
An effective data strategy ensures that data can be managed, moved, used and shared easily and efficiently across the entire organization. By establishing unified solutions and processes, a data strategy ensures that all data-related goals and objectives are aligned.
Without a data strategy, different parts of the organization will likely view some data-related capabilities differently which can lead to duplicated data and data infrastructures across the organization.
A data strategy is not an IT strategy, it’s a business strategy. Because it affects the whole organization’s data capabilities, you have to start with the organization’s aims, objectives and needs.
The organization’s leaders must drive the data strategy with the help of data specialists. This is because the data strategy enables organizations to answer questions which allows them to make forward-thinking decisions with less risk.
Starting a data analytics project
The approach we take toward our data analytics projects is determined by the data strategy. As organizations are constantly changing and adjusting due to changing priorities, requirements, and external market changes, we need to ensure our data strategy, i.e. our approach to data analytics projects, is constantly evaluated.
A data analytics project usually starts with either the executives having an idea or business problem they wish to address. They might also receive requests from other departments. It’s important to remember that the idea could come from anywhere within the organization.
The organization’s leadership will need to decide if the defined problem is aligned with the business goals and if the outcome will be profitable. They’ll work with the business and data teams to assess the viability of the project.
Data maturity
All of the above will vary depending on your level of organizational and data maturity. Data maturity is an indication of how embedded data analytics is within an organization. A high level of data maturity is the stage reached when data has woven its way deeply into the fabric of an organization and when data analytics has become incorporated into the operational and strategic decision-making process. That’s when an organization has become data-led.
We’ve covered the importance of becoming data-led and the processes we need to get there in detail. As a quick recap, here’s how, in simple terms, we arrive at making data-led business decisions…
- A business-led data strategy is put in place to ensure organizational unification
- Relevant data is gathered
- The gathered data is analyzed using the data analytics infrastructure
- If the data is reliable and the analysis is relevant, it should lead to a data-led business decision
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