Any great business begins with strategy, whether you're a large enterprise or a small, family-run company. In today’s world, any firm, no matter how large or little, in any industry requires a robust data plan. There are countless ways in which data science may benefit a firm. Nevertheless, if you wish to use data, you must always begin with a data plan. Let’s look at what constitutes a solid data strategy.
Company Strategy
A successful data plan should not be developed in isolation; rather, it should be guided by your entire company plan. As a result, the initial step in developing a data plan is to think about your organization’s strategic aims and critical business questions and objectives. Only then will you explore how you may utilize data to assist you in meeting those goals and answering business issues.
Priorities for Short-Term Adoption
Since large strategic data goals might take time to achieve and generate value, it is useful to identify a few quick; hopefully low-cost methods for you to offer value and show return on capital from data, which can help you win buy-in for more visible data use cases. You could, for example, conduct a customer churn study to assist in preventing or decreasing client turnover.
Data Requirements
Consider what data you will require to fulfill your objectives and where that data will originate from. This includes the following:
Data Management and Governance
Data science may provide huge benefits, but it could also be a severe liability if data security is not properly implemented. This stage prompts you to consider data quality, data protection, privacy and ownership concerns, transparency, and ethical data usage. Important factors to consider include:
Capacity and skills
The greatest impediment to organizations getting much out of data is the shortage of data knowledge and skills. As a result, this is a vital component of your data plan. Consider the following:
While there are several components to a data plan, it must start with an awareness of the fundamental problem(s) that must be solved. Too often companies with small teams try to replicate what works at large-scale data teams like Google. Understanding where your organization is allows you to select the right platforms and tools to set reasonable goals and expectations. With this critical insight, you will be better positioned to maximize the value data science can give to your organization.