Building a Software Data Strategy
Meeting the demands of the software customer in the digital economy requires incorporating big data insights into the design process quickly, and with agility. To ensure data is available and accessible to the advanced technologies needed to derive insights—such as analytics and artificial intelligence tools—software companies must first invest in a comprehensive data strategy.
Creating a data strategy is analogous to building a custom house— requiring thoughtful planning, a strong foundation, quality infrastructure, and active input from the homeowners. Executed properly, the structure will run smoothly, supporting and facilitating the lifestyle of inhabitants.
Blueprint for analysis
A house blueprint outlines rooms and spaces that serve a specific function and purpose, and this also holds true for data strategy. Data must be organized and structured according to the needs of the company.
The foundation of a big data strategy starts with assessing data requirements in relationship to the business as a whole. Software companies must first determine what information is needed to support the business strategy, guide cross-departmental decisions, and drive forward all aspects of the business. An assessment of current data sources and types will allow businesses to evaluate deltas and determine a course of action to obtain necessary data points.
For example, an app development company wishes to make highly relevant product recommendations to customers to drive usage and loyalty. The business already collects location and purchase information, but in order to deliver quality recommendations the company must incorporate usage data and demographic data as well. Data strategy will collect the required information, ensure the necessary data sets are organized, and can be readily accessed by a recommendation engine.
Flow of data
Once the blueprint and foundation are in place, the infrastructure of the house can be built. Data works like electricity in wires—once organized, it must be structured to facilitate the free flow and easy access of information. All departments benefit from proper data flow. Sales teams can leverage data to evaluate leads and gather customer intelligence, while product teams may use some of those same data points for real-time customer insights to generate new ideas and improve existing products to meet customer needs.
Software companies must use the blueprint to determine where and how the data needs to flow. Who needs access to what data and for what purpose? How often will the data be accessed and at what volume? By answering these questions, software companies can ensure not only does the data move freely to the required applications, but privacy is upheld be securing sensitive information, such as payment details, from access.
Developing a strong data infrastructure incorporates requirements from stakeholders from across the business - a good data strategy facilitates transparency through the sharing of data and insights.
Once the ideal framework is built and information flows as needed through piping and wiring, business can access and interact with data through applications as needed. For example, business intelligent applications can be built to better understand customer preferences and behaviors, which can then pave the way for predictive modeling and other advanced analytics.
A good data strategy also incorporates the applications of data— One of the key challenges faced by businesses is how data is obtained and linked to high-value decision making that improves ROI.
The ability to gain deeper data insight through real-time analytics gives software product and development teams useful insights to enrich product creation or advancements. Developers can enhance the efficiency of a product development cycle by leveraging a scalable data infrastructure, utilizing real-time analytics, and streamlining cross-departmental insights.
Bridge the skills gap
Technology is only as good as the people who use it—a house may have a state-of-the-art lighting system, but it does little good if home dwellers are unable to work the controls. It’s important that internal teams have a full understanding of utilizing advanced analytics and where to look for insights. Teams involved in the data strategy process can make well-informed decisions that align with business goals and objectives. Internal development teams and employees must be educated on maximizing capabilities of an elevated data strategy. This is achieved by end-users working in tandem teams executing new data strategies and building the data infrastructure.
Utilization of big data can serve as a company’s competitive edge. SoftServe's specialist teams can assist in the ideation, creation, and acceleration of new data strategies that leverage enhanced data infrastructures, and deliver value to an organization.
Read our whitepaper to learn more about how big data analytics can drive innovation: Customer-centric Products with Data-Led Software.