As a department leader, you understand what’s going on in your organization better than anyone else. No one’s closer to the work than you are or appreciates its complexities and nuances the way you do. But to be effective in your role, you’ve got to be agile and able to make strategic decisions in real time.
Of course, that’s easier said than done.
Unless you’re an analytics guru, you probably rely on your company’s data analysts to make sense of all the data you have and to turn it into actionable insights. And while that’s fine — data analysts rock when it comes to uncovering the insights hidden in your data — the problem is that relying on them can be a liability.
Here’s why: Data analysts are in high demand — and for good reason. They bring a critical skill set to virtually every business. Your go-to person for data analytics probably has a massive list of other requests to work through before they can get to yours. Truth be told, depending on the size of your business, it could take weeks, or even months, to get the answers you’re looking for. And while that might be all right for less pressing reports, if you want to move from reactive to proactive management, you need to be able to make strategic, data-driven decisions in real-time.
Compounding the analyst scarcity problem is that, once you get your initial question answered, you’ll discover several follow-up questions you didn’t anticipate. And while a data analyst might be able to answer some of those questions on the fly, if any of them go below the surface and require fresh analysis, they’ll wind up going right back into the queue. That means you’ll be waiting even longer to get answers to your new questions before the cycle begins all over again.
If you’re a marketing manager trying to decide how to allocate your budget next quarter, a sales manager trying to do forecasting, or anyone else who needs to make decisions using data, you know how frustrating this is. How comfortable are you making decisions today using insights gleaned from weeks- or months-old data?
Let’s be honest, although a few weeks is nothing in most contexts, when it comes to data collection, it’s practically a lifetime. Remember, new data is constantly flowing through your systems with the potential to change everything. So when the business decisions you’re making are based on point-in-time insights that can only offer you a rearview mirror perspective on what’s happening, you’re always at risk of being a step behind and out of touch with what’s going on in the business right now. And that’s just not good enough.
The answer to these pain points is enabling self-service for business leaders in the form of data visualizations.
If you want to move from reactive to proactive management, you need to be able to make strategic, data-driven decisions in real-time.
A Picture is Worth a Thousand Spreadsheets
Unless you’re an analyst by training, looking at a spreadsheet of analysis is not only too time-consuming but also too daunting. After all, who has the inclination or bandwidth to work their way through thousands of rows of data when there are a million other problems to solve right now? Not only are vast amounts of data difficult to navigate, finding the patterns hidden in that data and figuring out how those patterns fit together to yield valuable insights isn’t a skillset most people have.
Short of heading back to school or bribing your data analysts with fresh pastries every time you need something, the best way to get around this problem is by working with them to automate the creation of real-time data visualizations so you can make sense of your data on your own.
Remember, a picture is worth a thousand spreadsheets. Data visualizations help you identify trends and discover the stories hidden in your data. Not only is that helpful in terms of understanding what your data is telling you, but also when it comes to relaying that information to others. When the process of creating regular reports that are output in visual formats is automated, it means you don’t have to go back to your data analyst every time you need an updated analysis.
If you’re looking to do basic analysis on your data, there are a number of great data visualization tools that you can use, such as Tableau, Microsoft Power BI, Qlik, and ThoughtSpot. However, those tools are best suited to projects where your datasets are already in good shape for analysis. (Unfortunately, simple, clean data is more often the exception than the rule.)
More often than not, your data needs cleansing and you’ll want your analysts and data scientists to put it through more advanced paces like descriptive, predictive, or location-based analytics. In those scenarios, it’s important to marry one of those visualization tools with a powerful analytics platform. A modern, self-service Analytic Process Automation (APA)TM platform like Alteryx will give you the extra horsepower you’re looking for. This type of platform is perfect for analyzing disparate data sets housed across various locations, whether in the cloud or on-premises. And, using the platform’s connectors, it’s easy to automatically collect data no matter where it resides.
Greater Insights with Enriched Data
With the right platform, a data analyst can enrich your data with additional context from third-party sources, including:
High-resolution satellite images from DigitalGlobe with street overlays to provide a spatial frame of reference for your decision-making.
Lifestyle, attitude, brand preference, and media use data from Experian, as well as five-year projections, to accurately estimate customer demand today, tomorrow, and over the long term.
Visual presentations of more than 50 layers of cartographic data from TomTom, including roads, highways, and parks, to incorporate location intelligence data for more accurate analytic results.
More than 3,000 population characteristics from the 2010 United States Census, such as racial and ethnic information as well as family, household, and housing unit details to identify market potential and trends.
The result is better data, richer data visualizations, and more meaningful insights to help drive your department forward.
From Data to Insights to Visualization
Using an APA platform along with your favorite data visualization tool is incredibly easy and smart. All a data analyst has to do is access your data using the appropriate connector. Then, using simple, automated workflows, they can prep and blend the data to ensure it’s perfected before conducting your analysis.
Let's take a look at how the whole process works, from data to analysis to visualization:
And to be clear, this is something anyone can do — even you, if you had the time and inclination to learn. Great platforms have an intuitive drag-and-drop interface, which means that you don’t have to know how to code SQL to get the information you need. For analysts and data scientists who do like to code, look for a platform that’s code-free and code-friendly. There’s practically no limit to what they can do.
What’s In It for Me? The Benefits of Automating Data Visualization
Besides helping you look like a rockstar because you’re always in the know with up-to-date data analytics, working with a data analyst to automate visualizations has three main advantages:
1. It saves you a ton of time.
When you go to a data analyst with questions, you’ve got to spend time articulating your request, providing context, and relaying what it is you’re trying to achieve. And that’s not always trivial. Plus, you’ve got to wait to get the answers you’re looking for. If you’re using the right platform to help automate analysis to feed your data visualizations, not only are you in control, you can get the answers you need in minutes, rather than weeks. That’s a total game-changer.
2. You’re empowered to make better decisions.
Once you’re set up with your own data visualizations fed with real-time data, you’re able to get insights on demand about how things are going without having to wait in line for help from your analytics team. That means you can start making informed decisions based on the latest data available.
In the process, you’re bound to start thinking about the business in ways you never have before. You’ll spend more time considering how you can change your approach to achieve different outcomes. Ultimately, this will help you make better decisions and find innovative new ways of meeting your objectives, impressing your leadership, and making the best use of your team’s time. Over the long-term, that’s the kind of thing that’s going to catapult your career to the next level.
3. You can extract more value from the data science team.
While it’s great to no longer be stuck in your analytics team’s queue every time you need something, that’s not to say you should never engage with them. Rather, the point is to automate as much as you can and then go to them with bigger, more complex questions. When you’re no longer lining up for weekly reports, they have more capacity to focus on bigger, challenging questions, which is not only what they really enjoy doing, but also where they can provide the most value. That’s a win-win for everyone.
It’s also important to point out that automating data visualization is very scalable. That’s because, when you use the right tools and platforms, it allows for a lot more visibility into your thinking. That’s critical should someone else need to pick up your work at some point in the future. It also allows others to build on your work easily, or adapt what you’ve already created for their own needs so they don’t always have to reinvent the wheel.
APA and visualization platforms are like peanut butter and jelly — good alone, but exponentially better together.
The Road to Data-Driven Decision-Making
As a department leader, you’ve got a lot on your plate — more than you probably have time for. To be effective, you need to be able to get the data-driven insights necessary to make informed decisions. And you’ve got to be able to access those insights straight away.
While you can certainly go to a data analyst every time you need help, the fact is that can eat up a lot of time. A better solution is to work with your analyst to automate the process. By combining data visualization platforms like Tableau, Microsoft Power BI, Qlik, and ThoughtSpot with an analytics and data science platform like Alteryx, you can create powerful data analysis that feeds you visualizations and helps you make sense of all your data. Once set up, you’re off to the races without having to constantly tap data analysts for help.
The result is that you become much more efficient, make better business decisions, and use your analysts’ and data scientists’ time more strategically. We like to say that APA and visualization platforms are like peanut butter and jelly — good alone, but exponentially better together.
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