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The primary manifestation of this is expressed in English (or native country language). In service of report creation the job includes: Pulling data, writing queries, fulfilling ad-hoc requests, scheduling data outputs (reports, dashboards), liaising with script implementers / IT teams to collect more data, etc.Īnalysis Ninjas spend 75% or more of their time in analysis that delivers actionable insights. The primary manifestation of this is in creation of reports for their direct leader, or team or division or bunch of people. Reporting Squirrels spend 75% or more of their time in data production activities. Leaving people skills and capabilities aside, it is the work the employee does that makes them a Squirrel or a Ninja. Everyone hires what they believe are Analysis Ninjas. No company hires anyone called a Reporting Squirrel.
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You know what your Return on Analytics is!īefore we go too deep, let's get a couple of definitions right first. The organization functions off a clearly defined Digital Marketing & Measurement Model. Your organization structure for magic with numbers is: Centralized Decentralization. #4: The Analytics/Marketing skills in your Analysis Ninjas is 70/30. #5: 80% of your external consulting spend is focused super-hard analysis problems. #6: All automated reports are turned off on a random day/week/month each quarter to assess use/value. #7: 25% of all analytical effort is dedicated to data visualization/enhancing data's communicative power. #8: Your Team's DC, DR, DA effort allocation is 15%-20%-65%. #9: Your qualitative analysis practice rocks like crazy! #10: The KPIs in your DMMM reflect your company size/evolutionary stage. #11: Close to zero aggregated analysis exists, everything's segmented.
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#12: Almost all reporting is off custom reports. It is specific, it is, this will not surprise you, impactful. Each sign is essentially an action you can take, expectation you can set up. So in this post, let's look at twelve signs you can use as signals to identify if your organization is set up for magnificent success. Second… well there is no second, it is all about the big action and getting a big impact on your bottom-line from your big investment in analytics processes, consulting, people and tools. But a larger part of the reason is that companies don't quite make the right choices in what behavior to incentivize, they make mistakes when creating the organization structure, and in the expectations that are set for what success looks like.įirst… it is important to realize that big data's big imperative is driving big action.
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There is an analytics ladder of awesomeness each company needs to climb, and it just takes time. Yet, it is unclear if that increase in investment is being followed by a commensurate increase in value delivered to the organization's bottom-line.Ī part of reason for this mis-match in value delivered is that there is a natural evolution that needs to occur. Every indicator we have is that companies are investing more in every facet of analytics.