But in the sprint to collect, collect, collect, is it possible that most companies simply aren’t getting the most out of their data? The answer is a resounding yes. And it will only get worse.

App adoption is increasing all the time, with employees using an average of 110 SaaS apps for work, and more apps equals more data. All of that data must be stored somewhere, and compounding data collection can quickly turn into compounding storage costs. Companies can’t afford to shell out more budget for storage without corresponding return on investment. 

In an age of apps and data, how can IT leaders ensure that they are avoiding analysis paralysis and use that data to their advantage to enable insights across the company? To ensure data isn’t getting stale, companies can use analytics to turn collected data into data intelligence.

It’s time to dust off your data

Have you ever heard the old adage that if you haven’t used something in a year you should throw it away? While data doesn’t necessarily age poorly like that light fixture from the 1980s, the same concept still applies: If your data is collecting dust–and it probably is–then you should clean out your data closet to see what you have and how you can use it.

So where is the data coming from and where does it typically live? Collected data is typically broken out into four categories: personal, engagement, attitudinal, and behavioral:

• Personal data includes personally and non-personally identifiable information, such as a social security number or third-party cookies.
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• Engagement data is collected from places where customers interact with your brand, such as an app, website, or social media channel.
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• Attitudinal data highlights how your market feels about your brand and product and includes overall customer satisfaction metrics.
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• Behavioral data includes information such as purchase history.

Collected data is often stored in a number of disparate systems. A recent survey revealed that 30% of data is stored in internal data centers, 20% in third-party data centers, 19% in edge data centers or remote locations, and 9% is stored in other locations. In spite of the volume of data collected across locations, companies are collecting just over half of the data available. The same survey found that companies only collect 56% of available data through operations. Most of this data is siloed, causing redundancies. What’s worse, only 57% of collected data is actually used.

Because in this economy and business climate, companies are running so quickly that they are overlooking intelligence that can inform so many decisions–and save money.

Where data went wrong

How did companies get to the point where they have siloes of rich data but few insights? In a recent survey of IT leaders, 63% of respondents said data technologies deployed during the last three years have brought revenue gains and new business opportunities. But they’re now stuck. That same report revealed that 44% of IT leaders said that a lack of analytics skills is hindering progress. Why? Because in this economy and business climate, companies are running so quickly that they are overlooking intelligence that can inform so many decisions–and save money.

So what now? Data analytics. Fifty-five percent of IT leaders plan to increase investment into analytics capabilities over the next 12-18 months, an increase of 11% in just one year. And for good reason. By investing in tools and technologies to analyze data, companies can maximize insights and ROI. But tools and technologies are only half of the solution.

Want ROI from your data? Democratize data science

It’s easy to think that data science is for…data scientists. But new analytics tools are designed for users across the enterprise, creating a seamless and simple user experience in a no-code environment. When companies democratize data science tools and create a data-driven culture, that’s when magic happens.

Currently, IT leaders plan to focus 46% of their data and analytics budgets on recruiting new talent and upskilling existing team members because they realize that great data insights start with people. By encouraging inclusion, discussion, and education around how to leverage data and giving people the analytics tools they need to perform their own analyses, companies can dust off the data archives and enable users to extract insights.

Centralizing data not only lays the foundation for standardization and data quality, it enables data logs so users can identify trends and even use analytics tools to make predictions.

Get started to gain insights

The first step to democratizing data science and creating a culture that is ripe for analysis is centralizing data. Data should be a catalyst of collaboration for new projects, not siloed. Centralizing data not only lays the foundation for standardization and data quality, it enables data logs so users can identify trends and even use analytics tools to make predictions. Once data is centralized and standardized, companies can overlay analytics technologies on top of the infrastructure or repository. Not only does this ensure users are analyzing all available data, it increases the analysis accuracy.

In addition to centralizing data, companies must also make it easy for users to access and use that data, regardless of location. From cloud to edge technologies, there are a number of options available to create the right infrastructure that meets security, governance, and compliance standards on both organizational and team levels. 

The best way to get employees to start using data is to create a cross-functional resource team for knowledge sharing and alignment. This team can identify ways to tie data science and analytics to company functions and set appropriate goals.

Avoid analysis paralysis

At Lumos, we believe that there’s no such thing as too much data. It’s just that most companies are missing the tools to quickly and easily extract the right insights. They’re often paralyzed by analysis, spending time cleaning data and dumping it into spreadsheets…only to find out that the underlying data is already outdated. 

Our approach is that we want to help our customers use their data powers for good, which is why we provide every customer with a data-rich dashboard. The Lumos platform ingests your source of truth data and uses it multiple places in the app to supercharge workflows. Your data and our insights are then easily accessible in our dashboard, which not only delivers rich data points about key performance indicators, but actionable insights and key learnings that help guide you in your next steps. We start with the 30,000 foot view with a quick summary and then provide links to your next step so you can take action. Essentially, we help you put the data rubber to the road. 

While we provide you with a data-driven dashboard, Lumos goes one step further. We help you manage aspects of your data and analysis, going the extra mile to ensure you get the insights you need. This is something we strongly believe in, so we hope that you’ll consider adding it to your checklist when working with your own vendors and the data available to you. For example, we leverage data like last login to fuel automated alerts to deprovision users who may not be using their accounts, creating a self-sustaining process to continuously combat underutilized licenses. As well, our visibility over our customer’s key applications allows us to surface terminated, inactive, and unmatched accounts that they can act on immediately in our platform. Look for specific, automated ways via your own vendors where you can act on your data seamlessly.

Are you ready to learn which apps your employees are really using and make sure your provisioning and deprovisioning process is both secure and compliant? Let’s chat.

Connect with Lumos today.

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