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Business Costs of Using Legacy Data Analytics over Advanced Analytics  

Making any organizational change is challenging; making a successful change is even more so. Such is life. Newton’s first law of motion tells us objects will proceed at the same speed and in the same direction unless acted upon by an outside force. Translating this into business terms, it’s much easier to keep doing what you’re already doing than it is to introduce something new into your business workflow.

But continuing to take the path of least resistance, while seemingly simpler on the surface, can lead to stagnation. Sometimes disruption is exactly what an organization needs to improve its operations.

This principle is very apparent in the world of data analytics. There are real business costs of continuing to use legacy data analytics rather than adopting the advanced analytics tools now available on the market. Here are four significant costs of sticking with legacy business intelligence (BI) to consider when crafting your data strategy. 

Cost #1: Slow, Limited Change

A company’s ability to adapt depends on employee ability to get the information necessary to make confident decisions that affect operations. But many organizations are finding themselves limited by their analytics infrastructure.

One financial services director calls this a “technical debt” because data sources and system architectures like these that tend to “require burdensome technical support, do not easily integrate with other systems and are generally painful to work on and expand.” The result is a lack of ability for users to get the data-driven insights they need to make decisions, especially long-term ones. These limitations cause the businesses themselves to suffer, but it’s also a huge blow to employee morale because they face such obstacles in effectively working with company data.

Cost #2: Low Adoption Rates

As mentioned above, employees are loath to use cumbersome, restrictive, complicated or slow data analytics tools. This is why many organizations experience BI adoption rates below what they’d like to see—employees simply don’t see the value in using tools that seem like more trouble than they’re worth.

According to one survey administered by Gartner, BI and analytics adoption “remains elusive,” around 30 percent of all employees. The firm notes how ease of use ultimately impacts adoption rates, and that this is key because it directly correlates to business impact. In other words, organizations aiming to improve real business outcomes must consider how their legacy systems are potentially hindering adoption, thus holding them back from their goals.

Advanced analytics from providers like ThoughtSpot consider the non-technical user experience—allowing employees outside the IT team to ask their own questions by typing in simple queries or even using conversational analytics to ask verbally. Answers are available in seconds or minutes, and they come back in the form of a best-fit interactive chart, which saves employees the additional hassle of wrangling Excel tables into manual models.

All these features available today represent improvements over many legacy systems, which would require users to work through data/IT teams to pull answers and give less consideration to the user experience—which has historically hampered adoption rates. 

IT Reporting Backlogs

When the responsibility of querying data and creating reports falls on a centralized data/IT team, backlogs tend to spring up. After all, these employees only have so much time in each day, and they’re working within the limitations of legacy tech. Backlogs hinder how effectively companies are able to turn insights into action. Plus, they’re downright frustrating for everyone involved.

Implementing advanced analytics frees up data specialists to work on strategic, higher-order data projects like predictive analytics — while empowering non-technical employees to pull their own insights on an as-needed basis.

Failed Monetization of Data

What do you get when you combine a subpar analytics user experience, reporting bottlenecks, low adoption and difficulty converting stored data into tangible insights? You’re looking at failed opportunities to monetize data.

Slower Organizational Growth

According to Forrester, insight-driven businesses around the world grow by more than 30 per cent annually because these “customer-obsessed firms systematically harness insights across their organization and implement them to create competitive advantage through software.”

Organizations forgoing the upgrade to advanced analytics are missing out on the growth-driving benefits of better business insights, period.

Advancing your company’s approach to analytics does require an investment of time and effort to lay the foundation. And there will be an initial learning curve. But when executed successfully, you’ll be able to avoid these significant costs of continuing to rely on legacy BI.

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