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SmartData Collective > Data Management > Best Practices > How to Make Your Department More Data-Friendly
Best PracticesBig DataBusiness Intelligence

How to Make Your Department More Data-Friendly

rishi09
rishi09
8 Min Read
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ImageIt seems as though the entire world is abuzz about big data. If you get data alerts from Google much like I do, these are the headlines that fly over your radar every day: 

Contents
1. Step Back 2. Question3. Process & Analyze4. Search5. Educate

ImageIt seems as though the entire world is abuzz about big data. If you get data alerts from Google much like I do, these are the headlines that fly over your radar every day: 

  • Chinese Data Don’t Add Up [WSJ]
  • Can Data Analytics Make Teachers Better Educators? [CIO]
  • Scientists Question the Big Price Tags of Big Data [Newsweek]
  • According to U.S. Big Data, We Won The Vietnam War [Forbes]
  • Can Big Data Cure Cancer? [Fortune]

In other words, big data is doing big things – or it isn’t. That’s the general sentiment across all industries when it comes to the topic and many professionals are coming up against the same questions: Is big data worth it? Does it produce ROI? Is it just a phase? Will data become an asset? Who are the major players? Does any of it matter?

For most of us, it’s easy to see that the answer is, “Yes, big data does matter.” Tactically speaking, however, the proof is in the pudding, meaning that unless you utilize your data in ways that will make it matter, it won’t. What data needs is a strategy because on its own, its just fills up rows of spreadsheets through which not even the most organized among us would want to filter.

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Of course, most organizations or businesses aim to be data-driven. In reality, though, decision-makers aren’t the ones primarily using the data. They are instead at the receiving end, where the effectiveness of a data-driven strategy is polished into pretty presentations. 

We’re not here to focus on them. Instead, we’re here to focus on the pieces of the business using the data on a day-to-day basis to not only do their jobs better but also do them more effectively. And we’re here for them to provide something rarely seen when it comes to big data productivity: a game plan. 

See, there’s a simple way to get started and make your department more data-driven in the process, and it begins with these five steps. 

1. Step Back 

As a manager with direct reports or someone in charge of a core business function, it becomes too easy to get bogged down in the minutiae of everyday work. Ask yourself: “What are my professional goals for the next year?” Write these down on a piece of paper. It’s perfectly ok if they’re a bit vague. Starting with this question will put you in the proper mindset for the following steps. 

2. Question

Ask the following questions to yourself or members of your team. Feel free to use our email template below… 

Hi [Team Member],

I’m working on an initiative to make our department more data-conscious in order to help us reach our goals. Whenever you get a moment, please answer the following questions as honestly as possible. There are no wrong answers. 

  • What data do you frequently (daily, weekly, or monthly) use to make decisions or do your job?
  • How do you access that data? 
  • How much time does it take you to access it? 
  • How much of it is stored in multiple locations (i.e. pulling multiple reports and combining them)? 
  • What percent of your time do you spend pulling and combining reports versus doing analysis? If you spend more time pulling this information, we need to know so we can improve that process for you.
  • Do you think other departments or parts of the company have access to information that would be useful to you? If so, how would you go about getting it? 

3. Process & Analyze

Wait about a week for responses to trickle in. You’ll likely learn that your team spends much more time accessing data than it does analyzing it. This is a typical challenge for most organizations. The rise of big data has fueled an increase in utilized platforms, which in turn has created fragmentation in the market. Practically, it means your team spends more time navigating these technologies than it does using their outputs effectively. 

You will also notice that there is a lot of data stuck with other departments in the company. Again, the practical effect is that it takes your team time to find the right point of contact with that department, request specific information, receive a report that may not have exactly what is needed, and go through the process over again. Broadly, this means that your company is wasting its technology investments by not enabling differing departments to communicate with one another effectively. 

4. Search

When beginning your search for a technology partner, keep one question at the forefront of your mind: “Will this increase or decrease fragmentation in my department and my company?” In this case, err on the side of decreasing fragmentation. Search for technologies that are focused on unifying disparate silos of data and reducing the time it takes to pull and combine information.

5. Educate

The modern business is no longer going to be able to properly function as a conglomerate of individual departments. Cross-organizational collaboration and teamwork will be essential, especially when it comes to big data initiatives, and is why it is so essential that you begin creating a data-driven culture by eliminating fragmented software, platforms and the like. Implement an education plan that allows representatives from all departments to learn how to use the company-wide data platform for their own team-specific purposes, and also let them each explain how their department will best utilize the new information. 

This last piece is the most important because a data-driven company isn’t simply one in which the marketing department can notice trends and take action on them. It is one, instead, in which anyone in the company can find unknown adjacencies and properly report them to the department enabled to create revenue from such findings. 

This is how you make big data an asset on your balance sheet: by empowering an entire organization to use the natural human curiosity within it to its benefit. 

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