{"id":25524,"date":"2021-01-21T06:00:29","date_gmt":"2021-01-21T14:00:29","guid":{"rendered":"https:\/\/insidebigdata.com\/?p=25524"},"modified":"2021-01-22T09:08:39","modified_gmt":"2021-01-22T17:08:39","slug":"panel-discussion-needed-data-skills-for-2021","status":"publish","type":"post","link":"https:\/\/insidebigdata.com\/2021\/01\/21\/panel-discussion-needed-data-skills-for-2021\/","title":{"rendered":"Panel Discussion: Needed Data Skills for 2021"},"content":{"rendered":"\n

As we rush headlong into 2021, the pressure to drive decisions and competitive advantage from data is exposing a new challenge: for most companies, the analytics bottleneck they now face is a people problem<\/a>. To overcome that challenge, companies are racing to build deeper expertise across the board.<\/p>\n\n\n\n

And it\u2019s not just hard data skills, either. In a recent Gartner report, their Analytics, BI, and Data Science team noted that<\/a>, \u201cData and analytics leaders must leverage the collective intelligence of the organization to compose effective and augmented analytics solutions.\u201d In other words, soft skills and business acumen are now paramount to hiring managers.<\/p>\n\n\n\n

To help both hiring managers and job seekers looking to fill these key roles, we sat down with a number of senior analytics leaders to get their perspectives on hiring, recruiting, and critical skills. You\u2019ll find their conversation below, full of insights and actionable recommendations from Ryan Dillon<\/a>, Head of Analytics at Intapp, Mike Doll<\/a>, Head of Data and Analytics at Udacity, Don Moore<\/a> at Kitu Super Coffee, and Charles Zhu<\/a>, Director Solutions at Sisu.<\/p>\n\n\n\n

First off, thanks to everyone for diving into this discussion with us. As you look at the open roles you\u2019re trying to fill now, what are the most critical hard and soft skills you look for in an interview?<\/strong><\/p>\n\n\n\n

Mike Doll, Head of Data & Analytics, Udacity<\/a>: Great talent can come from a variety of backgrounds and brings many types of knowledge and tools to the table. What really matters, then, is how they deploy those tools in a structured way to solve business problems. For hard skills, SQL and structured problem solving are a must-have to work with data. For soft skills, I look for different things at different levels. Communication and accountability is always important: all analysts must deliver reliably and work with stakeholders. For more senior analysts I look for demonstrations of creativity and influence.<\/p>\n\n\n\n

Ryan Dillon, Head of Analytics, Intapp<\/a>: I agree. When working with data, it\u2019s critical to be strong with the essential tools. However, it\u2019s easy to get caught up in the technology choices and lose sight of the business problem, which is the most important thing we\u2019re trying to solve. Business stakeholders don\u2019t care about what tool you used to get from A to B, as long as the destination provides them with something reliable and insightful. The most important soft skill I look for is analytical curiosity. I like someone who isn\u2019t afraid to test the null hypothesis, because thinking about it another way might uncover an area to improve, in turn increasing the value of the organization.<\/p>\n\n\n\n

Don Moore, Senior Business Insights Manager, Kitu Super Coffee<\/a>: The basics still apply. With the wide variety of data sources we depend on, there\u2019s a premium on great SQL acumen, but also advanced Excel and modeling tools. Particularly when you\u2019re working in tandem with finance and planning teams, knowing your way around Visual Basic, Pivots, and everyone\u2019s favorite\u2014VLOOKUP\u2014is key. On the soft side, one of the key things I look for is politeness and positivity. These are key cultural aspects we look for across Kitu, but they\u2019re particularly important when it comes to building rapport and trust across teams.  <\/p>\n\n\n\n

Charles Zhu, Director of Solutions Engineering, Sisu<\/a>: One critical thing for me is willingness to learn, as the role of the analyst is quickly shifting. At a start-up, we have \u201cfull-stack\u201d solutions engineers who not only have the core analyst skills of SQL and data frame manipulation, but have also picked up data engineering, statistics, and most importantly, the ins-and-outs of our clients\u2019 business models. Further, there are simulation questions to ask that test the curiosity of the analyst to acquire this trifecta of skills. One of my favorite business interview questions is to \u201cexplain the business model of your favorite app.<\/p>\n\n\n\n

Next, looking ahead, what do you predict will be the highest-demand skill-set in 2021 in your industry?<\/strong><\/p>\n\n\n\n

Ryan Dillon: I believe translation is so critical for the industry. Business stakeholders want an analytics partner who can highlight opportunities and risks for them. They want a partner who can provide insights in terms they understand. It is not good enough to be a SQL expert if you don\u2019t understand the problems facing the C-Suite and other functional leaders. Over time, I think technical skills will become a commodity. This means we need to go beyond the code, put on our business hats, and view the world from an operator\u2019s perspective.<\/p>\n\n\n\n

Don Moore: In today\u2019s at-home economy, more CPG brands are prioritizing online sales channels. This is a completely different realm for the conventional CPG analyst who is used to dealing with panel data and store portals. In my opinion, there will be a surge in demand for analysts with experience using out-of-the-box E-Commerce Analysis Tools, and who are familiar with standard metrics and analyses in the E-Comm space. This raises the point that there may also be high demand for Data Engineers with knowledge of ETL, Data Warehousing, & BI tools, but this would be a bigger step for the industry, generally speaking.<\/p>\n\n\n\n

Mike Doll: I don’t have reason to believe that 2021 will be much different than 2020.  At a basic level, SQL, Python\/R and data visualization skills form the foundation of good analysts and data scientists. As the foundation, they will remain in high demand.

At a higher level, what will make an individual in higher demand is creativity and critical thinking. The skill of combining business acumen with technical expertise to deploy data in a way that truly drives value, that remains the hardest to find and therefore the highest demand skill-set.<\/p>\n\n\n\n

Charles Zhu: SaaS tools have expanded the potential of an analyst. A substantial chunk of data engineering, for example, is now doable by analysts armed with SQL, especially for companies born on the cloud. So for startups, we can imagine that the full stack analyst will hold off the need for a data engineer. Looking further out, we don\u2019t see the trend stopping so like Ryan, we see data translation, action recommendation, and business presentation skills commanding an increasing premium.<\/p>\n\n\n\n

When you\u2019re looking at a candidate\u2019s Linkedin profile or resume, what characteristics stand out most?<\/strong><\/p>\n\n\n\n

Don Moore: There are a few key things I look for in an initial scan of candidate\u2019s profile. First, whether or not they have a degree in a quantitative field, the most important thing is to show that they have experience working with data, have a metrics-first approach, and have hands-on depth transforming and visualizing data from multiple sources into a polished deliverable. Beyond that, we\u2019re interviewing for people who are self-motivated in their endeavors and can add value that we didn\u2019t originally intend or expect.<\/p>\n\n\n\n

Ryan Dillon: One of the best resumes I\u2019ve seen recently was also the simplest. This candidate simply listed three business problems, the related actions, and the business solutions\/results. It was a resume after my own heart. We often get caught up in the technical skills, but as analytics professionals, we\u2019re problem solvers first. This resume communicated that notion perfectly.

Another thing I look for is communication ability. We often work with lots of data and perform lots of analysis, ranging from simple to complex. Still, it\u2019s important that we\u2019re able to configure analyses to the appropriate level.  I\u2019m always captivated by candidates that are able to describe business problems in a relatable way. Questions such as, \u201cHow can we better estimate our new sales in the quarter?\u201d are relatable, and sometimes the analysis approach is transferable.<\/p>\n\n\n\n

Mike Doll: The characteristic I most look for in a candidate profile is evidence of business partnerships. I want to see specifics on how they deploy data in direct support of business outcomes. Just creating datasets, building reports, and crunching numbers is not evidence of real analysis. Neither is purely fielding requests or just handing over an output. I look for stories about how the analyst was a partner to some business function, be it marketing, sales, product, etc, and helped create value.<\/p>\n\n\n\n

Finally, we all know the best way to level up your function is to invest in the existing team. What skills are you planning to help your team develop in 2021?<\/strong><\/p>\n\n\n\n

Mike Doll: For my team, we\u2019ll continue to invest in a mixture of the partnership skills I\u2019ve mentioned, as well as a variety of technical skills. Analysts want to improve their integration with their part of the business, their presentation and influence skills and their understanding of the business itself. And then we\u2019ll also focus on improving skills in areas like statistical analysis, scripts like python, and model building.<\/p>\n\n\n\n

Ryan Dillon: My team, including myself, will focus on the concepts I\u2019ve mentioned so far. The more we\u2019re able to elevate our translation and communication abilities, the more we earn the trust of our business stakeholders. The more trust we earn, the more problems we\u2019re offered to solve. The more problems we solve, the more value we create for the organization. <\/p>\n\n\n\n

Don Moore: I\u2019m going to go further afield, and a little against the grain with this one. One of my biggest priorities in 2021 is expanding data literacy (and some basic Excel savvy) beyond my direct team. So, we\u2019re going deep on Pivot Tables! As a small CPG company, we\u2019re required to effectively communicate data to sell our products, but our employees are, for the most part, inexperienced in transforming data to paint that clear picture. By teaching all our employees to create Pivot Tables will enable them to rely less on our data team, make better use of provided data, and be better storytellers themselves.<\/p>\n\n\n\n

Charles Zhu: As others have mentioned, the most sophisticated analyses mean nothing if business users can\u2019t understand the insights. On the actionability angle, we have found that the data can show millions of interesting facts, but a very small subset can actually be acted upon, and even fewer result in permanent changes in operations. We have the privilege of analyzing diverse data sets across a variety of industries, so building a library of best practices for the kind of insights that can lead to immediate ROI is critical for us.<\/p>\n\n\n\n

About the Author<\/strong><\/p>\n\n\n\n

Grant Shirk is the Head of Marketing at Sisu<\/a>, where he is focused on helping global businesses diagnose why their critical business metrics are changing. An expert in product positioning, enterprise SaaS, and demand generation, he\u2019s helped brands like Fidelity Investments, UPS, USAA, and Viacom design and deliver elegant, intuitive, and useful solutions to tough business challenges. Prior to Sisu, Grant built highly efficient product and marketing teams at Scout RFP, Vera, Box, Microsoft, and Tellme Networks, with a focus on unique positioning and rich customer-driven storytelling. Grant holds a Bachelor of Arts degree in History from Stanford University.<\/em><\/p>\n\n\n\n

Sign up for the free insideBIGDATA newsletter<\/a>.<\/em><\/p>\n\n\n\n

Join us on Twitter: @InsideBigData1 \u2013 https:\/\/twitter.com\/InsideBigData1<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

In this panel discussion article, Grant Shirk, Head of Marketing at Sisu, to help both hiring managers and job seekers looking to fill these key roles, sat down with a number of senior analytics leaders to get their perspectives on hiring, recruiting, and critical skills. 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