What I Heard at Pink17: Which Comes First, Data or Analytics?

In Analytics, Data

I just returned from Pink17 in Vegas, which was yet another hectic but successful event for the Numerify team. The turnout included some big exhibitors: Atlassian was there with their interactive magnets to help you highlight your organization’s pain points; BMC had their bright orange booth and their troll stress dolls; and of course our partners at ServiceNow were there streaming demos from their booth on Facebook Live. And in the corner, you saw us, with our bright (and might I add, very comfortable) grapefruit sneakers and bright orange bags. There I was with a scanner and stamp in hand, ready to strike up a conversation with event attendees about the challenges their IT teams are currently facing.

Now that the dust has settled, I wanted to sit down and reflect on what I learned from the show floor this year. As the three days passed by, I saw a few themes emerge in my conversations with IT leaders, managers, and service desk folks on the show floor.
 

1. Data, Data Everywhere

One comment I heard again and again is that organizations have too much data. The Numerify team hears this a lot: IT organizations complain about having too much data and too little insight. And these IT leaders aren’t alone in facing the issue. PwC’s Global Data and Analytics Survey from 2016 reports that half of top executives (52 percent) will discount data presented to them when the data is not explained clearly — illustrating the fact that organizations don’t know what do with the overload of data.

While it’s true that many organizations don’t know what to do with their data, we also know that they want to make data-driven decisions and agendas. The same PwC Survey revealed that the majority of senior executives (61 percent) acknowledge their companies could rely on data analytics more and intuition less. Leaders may have great intuition, but they should not be afraid to use their data, and pinpoint the strengths and weaknesses within.
 

2. Scrub a Dub Dub that Data

Another idea that came up was how organizations think their first move should be finding “the right” enterprise management system. IT leaders want to “clean” the data, which they associate with being necessary to focus on what is important. With legacy systems, it’s hard to sort data or even upgrade to other enterprise management systems. This seems to be one of the leading obstacles and objections to investing in analytics.

Many IT leaders have this notion that before they can unlock their data insights, they need to perfectly organize their systems and infrastructure. This is a myth we need to nip in the bud — because how can CIOs and IT leaders know what is important to focus on? By trying to just deal with an abundance of data without analytics, IT executives will find correlations that reinforce their preexisting notions, instead of learning from their data. They fall into the black hole of trusting their gut alone. Yet IT leaders with data sorting challenges are not alone. In Deloitte’s report “The Analytics Advantage,” 32 percent of respondents admit to having no centralized approach to capturing or analyzing data.

In response to these objections, I want to share with you what I shared with the folks on the show floor:
 

Why should Analytics be your first step?

Instead of focusing on the problem of having data clutter, IT organizations will attain greater value in the long run by refocusing their attention to their goals (i.e. how do you want to utilize your data). With 2.5 quintillion bytes of data created worldwide every day, it has become virtually impossible to clean up all of your data. Having structure is great, but it’s the insights from your data that can truly help you develop a stronger, more effective structure.
 

Where do you go from here?

For an analytics deployment to be successful, the key is to create and implement a plan. Even for organizations that do not know how to efficiently leverage their data (you know who you are), you can start by creating a culture around information. The beauty is that less is more — you don’t need ALL of your data, just some of it. Once you separate out the metrics that matter, you can help frame the objectives in your organization and help your team ask the right questions.

I am assuming you are familiar with the quote “It’s not what you know; It’s what you do with what you know.” So the next time you feel bogged down by the copious amounts of data on your hands, remember that analytics can be a solution to your messy data problem — but it will only get you so far.

A great first step would be downloading our latest eBook, The Case for IT Analytics.

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