How To Develop an Analytic Strategy in 4 Steps (With Tips)
By Indeed Editorial Team
Published March 17, 2022
The Indeed Editorial Team comprises a diverse and talented team of writers, researchers and subject matter experts equipped with Indeed's data and insights to deliver useful tips to help guide your career journey.
Leadership at companies often creates various strategies to help them reach individual business goals. One of these strategies might include analytics, where companies focus on data to understand different areas of their performance. Learning about this type of strategy can help you understand why organizations benefit from investing time in creating one. In this article, we discuss what an analytic strategy is and share key details about it, like why it's important, how to develop one and some tips on the subject.
Related: 12 Decision-Making Strategies
What is an analytic strategy?
An analytic strategy is how companies decide what they do based on the information they gather. This means connecting the data you might gather to overall company goals. You can understand possible opportunities for achieving these goals with three components:
Analytic operations: Analytic operations are the processes that companies use to gather and analyze data.
Analytic infrastructure: Analytic infrastructure includes the systems and tools that companies use when gathering data.
Analytic models: Analytic models are how you might visualize or categorize data elements. Models can be descriptive, diagnostic, predictive and prescriptive.
Why is an analytic strategy important?
There are several reasons this kind of strategy is important, such as:
Improving your products: Data can help you learn how your customers use your products or services. With an analytic strategy, you can learn about these uses and how you might improve them to solve more problems for customers.
Understanding your performance: Besides specific customer needs, one strategy you might implement is to understand how your business performs. You can learn what factors affect business and what changes you might make to improve performance.
Understanding customers: You can also understand your customers beyond your products, including how they behave. With a targeted strategy, you can learn the best ways to deploy marketing and sales efforts to reach more customers or engage them better.
Analyzing markets: By analyzing markets, you can understand the potential impact of your strategies. This means understanding the competition's performances, your market positioning and common trends to achieve your business goals.
Reducing bias: As companies might hope to see more positive information when reviewing figures, analytic strategies can help reduce bias. This means using real-life examples when testing to ensure predictive models are accurate.
How to develop an analytic strategy
Here are some steps you can take to develop an analytic strategy:
1. Evaluate current capabilities
Evaluating your capabilities means reviewing what software, tools and processes you have to work with analytics. This can also involve reviewing the team members you hope to include when strategizing or gathering and visualizing data. By understanding how you can find and manage data, you can assign responsibilities and timelines to achieve your goals. Here, you can also identify the infrastructure of the company and data processes to ensure nontechnical people can analyze data or have the tools to gather data themselves.
2. Review company goals
It's important to understand your company goals to learn what data you need and what you want to do with it. For example, if your goals are to increase sales numbers by a certain percentage, you can research best-selling products, market performance and trends. This might also mean understanding company metrics, like key performance indicators (KPIs) and the ideal scores for each. When analyzing your company goals, you can review several strategies implemented before to understand the different effects of each.
3. Gather data
Once you understand the capabilities and goals of your organization, you can gather data. This might involve data mining from several sources. For example, you can get customer information from your customer databases, advertising metrics and social accounts. During this stage, you can also perform testing to see how possible changes to your business activities affect your outcomes. This can help you understand if you need unique data points to decide on your actions.
Reporting can be essential at this stage, as you might produce regular reports to identify any changes. As the purpose of analytic strategies is to learn whether your predictive metrics are appropriate, your reports can show if there are more effective ways to manage your actions.
4. Determine solutions
You might determine several solutions after gathering and analyzing your data. These can involve additional strategies around data collection methods and tools. For example, you might determine you want a better way to automate gathering data from various locations. As this activity can help you identify gaps in your data, these strategies can help you get more targeted information. This type of solution focuses on your overall data infrastructure and models.
Another solution might be to adjust your business activities to better align with company goals. After performing tests and reviewing regular reports, you can see how different decisions can affect outcomes. For example, you might discover that a certain advertisement placement is the primary source of website visits, so you can try to leverage that more in different areas.
Tips for analytic strategies
Here are some tips you can use when working with these strategies:
Create a roadmap: Creating a roadmap can help you track your progress on creating and implementing analytic strategies. This can include key milestones, like when you'll define goals and capabilities and when you might perform tests.
Consider outside assistance: Outside consulting firms can help you create and implement this type of strategy. Hiring these to help review your data can also help eliminate any bias your organization might have.
Evaluate company culture: Accurate data is important for all strategic decisions, so you might evaluate your organization's culture to understand if people understand their roles. You can also ensure teams know business goals and how analysis can support them.
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