Why Your Software Needs to Do More with the Data It Collects

Companies are exploring ways to use data to gain a competitive edge – and ISVs that facilitate it may capture more business of their own.

data visualization

Accessing comprehensive data enables organizations to develop high-level and granular insights to make well-informed decisions to best support the end user. However, Amoi Dalvi, VP of Product at Nerdio, points out that without clean and robust datasets, organizations will struggle to pinpoint areas of opportunity for improved utilization and cost savings.

Dalvi shares his insights on how ISVs can provide more value to clients by providing access to software data.

How can using data from business applications help customers/users?

Dalvi: Data can best be used in the following ways to help drive business efficiencies:

      • Optimizing end-user analytics: Today, end-user analytics are imperative for organizations to understand to build efficient and effective operations. With an increased demand for optimal business applications, organizations must have an understanding of the influx of user data in order to build the best possible experience for today’s digital workforce, which, in turn, will translate to more optimal business results.
      • Spotting inefficiencies: Data provides the blueprint for understanding how to improve business outcomes. This is because data increases visibility, illuminates key trends and patterns, and reveals inefficiencies. When organizations leverage data-driven insights, it helps them improve their operational processes to navigate both internal and external headwinds better.
      • Increasing cost-conscious decision-making: During economic uncertainty, cost-savings are a top-of-mind priority. And data is the way for organizations to know where they can optimize costs and reduce inefficient spending. Analyzing data helps leaders create cost-cutting strategies to improve efficiency.

What advice do you offer for making data available for analytics?

Dalvi: When making data available for analytics, it’s essential for organizations to maintain high data quality to yield meaningful results. This process starts with organizations ensuring that the data they collect is free from errors, inconsistencies, and duplicates, as these can skew the analysis and lead to unreliable conclusions. Furthermore, organizations must collect up-to-date insights to drive real-time decision-making. Other considerations organizations can leverage include:

  • Developing a data strategy: Organizations can define their goals and objectives for incorporating data into their business functions, making it easier to determine next steps and deliver on KPIs. Moreover, when developing a data plan, organizations need to outline how data will be collected, stored, cleaned, and utilized for analytics, so the process is organized and leads to a seamless integration of data and analytics.
      • Prioritizing data governance: Establishing clear data governance policies and procedures helps maintain data quality over time. Regular audits, validation checks, and updates to data standards contribute to a continuous improvement cycle, preventing data degradation and ensuring long-term analytical value.
      • Collaborating with data experts: Organizations should consider working with industry experts to understand the nuances of how to prepare data for analytics. These sources can also help organizations understand best practices and unlock the hidden value in the data.

Do you advise software companies to integrate or embed analytics tools with their software?

Dalvi: Software companies should consider integrating analytics tools into their products. More organizations want to gain value from their data, but without the right tools or training, it’s difficult for businesses to garner the insights they need. When analytic capabilities are embedded into the tools they already use, it increases their visibility into their operations, helping them make more informed decisions faster and more effectively.

Is this a trend that will make software more attractive and competitive?

Dalvi: Adding analytics tools into software is a competitive advantage. Just like what’s happening now with companies adding AI capabilities into their tech stack, the same is true for organizations integrating analytics into their existing software. The ability to evaluate data in real time allows businesses to respond faster to market changes, capitalize on emerging trends, and deliver precise solutions to end users.

Any final words on the value of enabling businesses to leverage data from their software?

Dalvi: Organizations of all sizes have faced many challenges these past few years. Whether moving to remote work and then back to the office or facing increased pressure from economic uncertainty, businesses have completely transformed. This has forced IT and C-suite leaders to re-evaluate their technology investments and make decisions based on the most optimal tech stacks out there. Evaluating software for its ability to accurately and efficiently collect and utilize user data is crucial to ensuring performance is optimized and cost-efficient. In today’s modern world, this is becoming an increasingly important metric for company leaders.