Ruby Sundays
Welcome to the first post of our series, Ruby Sundays, where you can learn more about Ruby Research, our work, and our menu of services.
My favorite article to share with business leaders interested in getting started with analytics was penned by Google’s Chief Decision Scientist Cassie Kozyrkov, “What Great Data Analysts Do — and Why Every Organization Needs Them.”
It explains why an organization’s first data team hire should be an analyst. Not a data scientist or a statistician or a machine learning / AI engineer.
Why?
Because great analysts are excellent at making sense of the data we create, use, and maintain. They help managers to leverage insights from current data to boost revenue, find efficiencies, and pinpoint strategy pivots in real time. They are adept at mastering business contexts and can assist many functional teams.
If you haven’t read this article yet, I’d recommend doing so.
Since this article was written in 2018, the field has hushed the hype that the data scientist is every organization’s cure-all. There is a growing consensus that what’s required for sustained success in analytics strategy over time is a team, one with a variety of expertise brought to bear on leadership’s top challenges. Any given analytical project might leverage one or more of the following key players*:
Analysts (salary range: $47,500 - $81,000)
Data scientists ($92,500 - $138,500)
Statisticians ($78,000 - $112,500)
Machine learning engineers ($103,000 - $149,000)
Data engineers ($96,000 - $142,500)
Data architects ($110,000 - $152,500)
Software engineers ($80,000 - $116,500)
Business analysts ($62,000 - $98,000)
Project managers ($54,500 - $95,000)
Why did I include the salary range of each of these positions? Because building this type of capacity is expensive. This is the reason why, lately, we see them mostly at large companies like Netflix.
But what if it were possible for the little guys to leverage analytics too? Ruby Research wants to make this possible by bringing companies the right analytical talent at the right time to the right projects that will deliver the highest value. How do we do this? We help organizations scope work into bite-sized analytics projects that we can help them to tackle one by one, over time.
Menu of Services: Analytics
In the Analytics service area, Ruby Research strives to do two important things well:
Collaborate with business leaders to explore and scope viable analytics projects, those appropriate for that organization’s data on hand and analytical maturity. The services you’ll need from us at Ruby Research will depend on your greatest challenges today. Are you eager to improve your product? To develop metrics to guide your sales team? Compare the success of this year’s marketing campaigns to last year’s? What you can accomplish with research & analytics depends on an assessment of the data you currently create and maintain.
Mobilize seasoned data and analytics experts and support teams to complete analytics projects. Based on project needs, Ruby recruits working teams to gig for each project based on team members’ demonstrated capabilities; and these teams commit to the delivery of high-value analyses and data products scoped.
Which types of analytical challenges have managers shared with us at Ruby Research? How might Ruby Research work for them and for you? Stay tuned next Ruby Sunday.
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* Occupational salary information is the 25th percentile to 75th percentile range for each occupational salary in the United States reported by Ziprecruiter.com on August 1, 2021.
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To learn more about analytics and data science from Cassie Kozyrkov, follow @quaesita on Twitter.
Ruby Research is a research & analytics consultancy that puts data to work. We help leaders to study and improve products and services; set goals, metrics, and KPIs; analyze and forecast performance; build dashboards for real-time insights; and evaluate programs and offerings.
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To learn more about Ruby Research, our work, and our menu of services, follow @rubyresearcher on Twitter, Facebook, and LinkedIn.
