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Prioritizing Requests for Data Analytics

Posted by Colleen Balda on Jan 15, 2018 12:00:00 PM

From small mom-and-pop businesses to a multi-billion dollar franchises, big data and analytics appeal to everyone looking to improve their insights to better understand clientele and make more informed business decisions. Whether it’s the IT guy, the director of marketing, the company CPA or the vice president of operations – each role needs a lot:

 

 

  • They need data that’s simple and easy to understand
  • They need the data immediately
  • They need the data to be real-time

It might seem like urgent requests require urgent responses, but when everything is a top priority, how can anyone possibly prioritize? In situations like this, the right course of action normally isn’t reactive acceptance, but instead taking a step back to reaffirm your customers’ data objectives.

Don't Be Afraid to Push Back and Ask Questions

The entire purpose of big data and analytics is to drive informed decision-making to achieve the goals of the organization. Every company that wants to integrate a big data or business intelligence and analytics solution should do so with this purpose in the forefront.

If you find that a customer is receiving too many requests for data or they’re being spread too thinly, encourage them to push back a little with these questions:  

  1. Why do you need this data?
  2. What actionable business decisions do you intend to make based on the analytics provided by your solution?
  3. Does this request align with your department’s overall strategy and the organization’s key performance indicators (KPIs)?

If someone in your customer’s organizations want to analyze data but cannot answer these simple questions about their intentions for the data, it’s probably not a productive use of the customers’ time and resources.

Understand the Difference Between Want and Need

There’s a monumental difference between wanting to know a number (i.e. yesterday’s venue attendance or sales numbers) just to be informed versus needing to know a number in order to make a decision that impacts the business.

Users of new big data implementations aren’t used to being asked why they need data or what they plan to do with the data. A data warehousing solution that’s implemented allows users access to data in new ways, but simply having access to data for data’s sake serves zero purpose.

Avoid Wasted Time and Efforts

Your customers might see this playing out in their organizations, whether they have started on an analytics journey or not.

For example, say a company has employees who spend most of their day compiling data reports. If that company doesn’t have an analytics solution, this might entail collecting data from siloed systems and consolidating everything into excel spreadsheets. These “reports” are then emailed around departments on distribution lists and sent to high-level executives.

However, if the data compiled isn’t actually needed (either because it’s not part of the strategy of the company, or it’s not a driver of actionable business decisions) then, despite the massive effort and time spent putting the data together, very few recipients of those “reports” actually even bother to open the email attachment. Even if the reports are reviewed, if the data isn’t part of the company’s bottom line, it’s safe to say it won’t impact the recipients who do see the information.

Reaffirming your customers’ data objectives can help you optimize their time and resources so that no one is wasting time on busy work that ultimately doesn’t affect the company.

Asking the Right Questions Helps Prioritize and Address the Right Requests

Simply asking why the data’s needed, what decisions will be made from the data and if the request aligns with the overall strategy will absolutely revolutionize the way your customers’ organizations think about data and the way its users optimize analytics.

Keeping these simple questions in mind and asking them without hesitation at all steps in the analytics journey is the No. 1 key to success as companies across industries become data-driven operations.

To learn more about how Tech Data’s data analytics and IoT team can help you deliver true business value, visit the Knowledge Network or reach out to your Tech Data account representative.

Colleen Balda:

Colleen Balda serves as a business consultant for Tech Data’s Big Data and Analytics team. She’s responsible for requirements gathering, business intelligence architecture, and report and dashboard visualization development of Tech Data IP and analytics offerings. She also works as a business analyst on projects, consulting and training clients on how to identify trends and patterns in the data they collect to optimize business operations and revenue.

Tags: Analytics, Internet of Things (IoT)

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