New Year's Resolutions of the Data Team

As 2017 draws to a close, many of us find ourselves reflecting on the year, assessing what went well, what didn't and why. Each New Year provides a symbolic opportunity to start anew or change something. Here's what some data team members have in mind:

Drive More Action

Time and time again, we're told that insights without action have little value. Along those lines, it can be frustrating to present analytical results only to have them fall on infertile ground.

For example, deep learning and AI startup Clootrack has a number of clients, all of whom are hungry for answers about business and product-related issues. However, Clootrack co-founder and CEO Shameel Abdulla said less than 20% of the suggestions the company makes get implemented.

"Many data teams will have the same story to tell, [about] how hard they toiled to ensure the correctness of data and presentation, [and then] at the end to be just another report in the mailbox," said Abdulla. "One thing we would like to see change badly, is all our data insights getting life in the form of actions."

Develop Better Presentation Skills

Analyses can be interpreted differently by different people. Sometimes, unnecessary gaps are created by data team members that have not yet learned how to communicate insights in business terms.

At boutique data strategy and analytics firm Salt IO, everyone agrees analytics initiatives struggle and they realize it's easy to blame the data, the tech, or the business when the situation could be helped by developing more effective communications skills.

"The inclination of most data team members might be to learn a new database or a new library or programming language," said Zac Ruiz founder of Salt IO. "Instead, start an internal team blog. Take one of your business stakeholders to lunch once a month. Ask to use your employee training allowance on a public speaking course or leadership coaching."

If data is the new oil and data team members are sitting on all of kinds of insights, then they have to find way to communicate more effectively, Ruiz said.

Move Beyond the Common "Analytics" Definition

Analytics represents just one aspect of the data lifecycle. While everyone acknowledges that the volume of data is exploding, not everyone knows what to do with it, and even if they do, they may not be getting data in a timely manner.

"Customer landscapes are changing too fast to keep using data in traditional forms, [such as] scorecards, look-back analysis, [and] silos," said Stacey LeBlanc, director of analytics at marketing agency POP. "It's about using data in real-time to make data driven decisions at the customer level. Data isn't just for the analysts anymore, it's available to entire organizations. We are armed with the tools -- 2018 will be about how we use them to drive the customer experience to new levels."

LeBlanc's 2018 wish is to start positioning analytics for what it is, which is much more than "analytics" which can be and sometimes is characterized as traditional descriptive (historical) reporting. With AI, machine learning, data mining and strategic analysis, analytics doesn't just provide insights about the past anymore. It's also enables insights into probable futures.

Improve Efficiency

Business is moving at such a fast pace today that data teams should be thinking more about reuse. For example, Ken McDonald, chief growth officer at sports team management app provider TeamSnap (who manages a small analytics team) wants to see easier access to data in the cloud. After all, businesses are using more SaaS products than ever which means their data is scattered all over the Internet. While some companies have APIs to access that data, it can take a lot of work to access cloud data sources and stitch them together.

"In 2018, I want to put more emphasis on reuse, reuse, reuse," said McDonald. "It's so easy to think of every analysis as a one-off that you just need to bang out. However, if you take a little more time to think about how to extend your standard data sources to incorporate this analysis and similar ones in the future, you can save a ton of time in the long run."

Jason Bauman, SEO specialist for personal injury law firm Console & Hollawell has a similar goal, albeit related to site traffic.

"My goal for the coming year is to unite all data sources into a single universal view," said Bauman. "Right now, we track things through a combination of Google Analytics, call tracking, form emails, and our internal metrics. These all have different methods for quantifying what is important and what isn't, [so] making comparisons is a time-intensive manual process."

His 2018 is to automate data collection, streamline manual entry, and then create a series of stakeholder dashboards that give each of his customers the information they want at a glance without burying them in data of no interest.

What's Your 2018 Resolution?

I'll start: Mine is to get people to interact more than they do when insights are presented. Too often, people sit back and nod in agreement with a conclusion or recommendation, but later it becomes obvious that there may be biases or desires that went unmentioned for some reason such as a lack of time, distraction or fear of embarrassment. How about you? We'd love to continue the discussion in the comments section.

Lisa Morgan, Freelance Writer

Lisa Morgan is a freelance writer who covers big data and BI for InformationWeek. She has contributed articles, reports, and other types of content to various publications and sites ranging from SD Times to the Economist Intelligent Unit. Frequent areas of coverage include big data, mobility, enterprise software, the cloud, software development, and emerging cultural issues affecting the C-suite.

New Year's Resolutions of the Data Team

As you look back on 2017, we're sure there are improvements you would want to make. Now, as we head into 2018, what changes are you planning?

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  • 12/29/2017 8:32:37 PM

Improving efficiency sounds like a great goal for the new year. It's exciting to see improvements like this. Worthy goals for all!!!

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  • 12/29/2017 11:19:58 PM

One action that I've found to be helpful is a careful review after a recommendation has been shelved - to really understand why. For this to work, you have to be past any tug-of-war. Tug-of-war is the stage where the business (for some unfathomable reason) doesn't want to implement your fabulous idea. Any discussions in this stage will still be somewhat less than forthright, as some parties may have an ax to grind.

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  • 12/30/2017 12:19:37 PM

Following up is important. To often we generate fabulous work to pass on and don't follow up. We often move on to the next best thing. As a result that wonderful work goes unfulfilled to its fullest.

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  • 12/30/2017 5:21:00 PM

rbaz, so true. Often, we are too busy in the modern office grind to stop and appreciate a great project, a job well done --- or in the very least, to do the proper follow-up with the client/business to ensure that they are as satisfied as you are with the end result, to gain valuable feedback, and hopefully some commendation that you can frame and hang on your wall!

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  • 12/30/2017 5:27:34 PM

Broadway, not only for recognition but to assist the user gets maximum use from your work. Who else knows more the full capabilities of your work other than you.

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  • 1/3/2018 10:15:39 AM

The follow-up is really important. What may look like aninitial discouraging result may look much better in 6 months- and visa versa.

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  • 1/3/2018 3:01:07 PM

The tendency to keep the status quo is a strong one. No wonder then that "less than 20% of the suggestions the company makes get implemented." It takes some strong "willpower" or at least leadership to keep moving forward sometimes when the evidence indicates changes are beneficial.

  • 1/5/2018 10:39:22 AM

I found this statement interesting: "However, Clootrack co-founder and CEO Shameel Abdulla said less than 20% of the suggestions the company makes get implemented."

It makes me wonder if the problem isn't necessarily with the audience but with the suggestions. Perhaps the data that they are based upon, or the algorithms themselves, or maybe there just are too many suggestions for an organization to absorb. Afterall, sometimes less is more.