The Role of Data Analytics in Business Decision Making

How Does Data Analytics Work Its Magic?

For starters, data analytics helps uncover hidden insights and trends lying deep within enterprise data stores. These insights may not be apparent to decision-makers at first glance. With analytics, they can drill down into the data and identify patterns or trends that point to critical focus areas. For example, a simple glance at a structured list of sales data can easily pull out a list of products or services that are not performing well. But the real challenge for leaders is to not find out the products that are not selling well, but they need to find out why the sales are low. This is where data analytics plays its magic.

A closer look at granular performance metrics of the product can reveal trends such as lower sales in a specific time frame or amongst a specific demographic of customers, fluctuating sales patterns for certain price points, etc. These help in making strategic decisions that help to rectify core business philosophies that bring down revenue or lower conversions in sales cycles.

The Role Of Data Analytics in Business Decision Making

Let us explore in detail 4 areas where data analytics can become a strategic driver of success in business decision-making:

Accelerate customer acquisition

Studies have shown that data-driven companies are 23 times more competitive in acquiring customers when compared to those that are not. The role of analytics begins by penetrating the business's historical data and creating a profile of customers who are most likely to buy their offerings. The classification may be done based on demographics, financial spending habits, gender-specific interests, local or linguistic preferences, and much more. There is so much data available in the market that helps guide businesses to tailor their market entry experience in a way that reciprocates with the interests of their intended customer base.

Data analytics can help break down patterns of behavior that best describe the interests of segregated customer groups and help decision-makers create customized entry plans for products and services aimed at each group.

Enhance operational efficiency

Legacy business practices and processes may often slow down growth in today’s hypercompetitive markets. Decision-makers could find it difficult to narrow down the source of inefficiencies if their operational ecosystem is diverse and expansive. Manually understanding the economics and dynamics of different workflows and processes to further create a roadmap of improvement can take months or years to complete. This is detrimental to growth as competitors with nimble and leaner operational capabilities can quickly respond to market sentiments.

With data analytics, however, it becomes easier to pinpoint sources of inefficiencies within the operational landscape of a business. Every process, workflow, employee activity, and departmental initiative can contribute data points that represent their participation in the revenue or operational cycle. This data, when analyzed with powerful analytics solutions, can unravel opportunities for improvement and scaling. This helps decision-makers prioritize investments in areas that matter and demand critical upgrades. Analytics helps in modeling scenarios where leaders can see a visual representation of how every change imparted affects business growth and can fine-tune their growth plans accordingly.

Strategically improve offerings

We have seen how data analytics can contribute to building seamless customer acquisition approaches and operational efficiencies in a business. Similarly, intelligence about customer preferences and the most efficient workflows can be used to further create engineering or delivery workflows for new products and services. These can be configured from the start to have features and characteristics that are customer-centric, take very minimal production or delivery time, have easy maintenance, and have longer revenue generation potential.

Such a level of strategic guidance in product or service development helps a business avoid costly mistakes and unsold inventories. This contributes to healthy revenue margins which provides enough leverage to invest further in R&D and other growth initiatives.

Lower risks

Data analytics uncovers not just opportunities within the business landscape but also pinpoints critical risks that can undermine performance and growth. These risks may be at a security level wherein data about breaches, incidents, etc. can help discover the root cause of security letdowns. It could be performance-related risks wherein analytics on product or service performance can unravel hidden risky behavior that is preventing further sales like for example, a glitch on the company website or unresolved issues with a channel partner or vendor, etc.

The risks may even be at a strategic level. For example, mistakes in financial management wherein the failure to consider anomalies and market dynamics in the budgeting process led to troubles. With data analytics, it becomes easier to model every possible business scenario and identify risks associated with different core pillars or departments.

Taking Decision-making to the Next Level

Data analytics can transform how organizations perceive their growth story in challenging markets. From discovering ways to sell their offerings better to eliminating inefficiencies and risks in operations, the roles played by data analytics are immense. However, adopting data analytics for decision-making is not an easy endeavor. Selecting the right tool, building the right data infrastructure, placing the right controls on data generation and acquisition, etc. are just a few of the several steps needed to ensure sustainable ROI.

This is where businesses need to leverage an experienced technology partner like Wissen to formulate their data analytics roadmap from scratch. Get in touch with us to know more.