Analytics: Embracing Ad Hoc Analytics at Scale with Soal

Mammoth Growth: Insights From The Trenches

Analytics teams are positioned to guide everyone in a company to make better decisions. But how well are companies measuring the performance of their analytics teams? What types of questions are they dealing with, and how do their actions impact the company’s growth trajectory?
We dive into these topics and much more in the latest episode of our podcast. Our CTO Drew Beaupre chats with Osman Ghandour, Co-Founder of Soal Data. Osman explains that ad hoc analytics refers to unplanned, reactive work that data and analytics teams often have to handle. While this type of work can easily be seen as a distraction, it can also be an opportunity for these teams to ease decision-making throughout a company. As Osman points out, there’s a fine line between resolving a one-time ask vs recognizing the types of questions that come up over and over again. Soal Data’s mission is to shine a light on all types of analytics questions, to show which ad hoc requests should be given more close attention. Drew clarifies their value this way: if analytics and data teams receive repeat ad hoc requests of a similar nature, there’s a much higher likelihood that those requests point to valuable areas for the business to focus on. Soal Data helps companies identify these patterns automatically. Think of their solution as analytics for your analytics.
Data and analytics teams can be structured in three distinct ways to address ad hoc requests:
No special structure. A company’s existing analytics and data teams must drop whatever they’re doing whenever an ad hoc request comes in. In this scenario, the same people must manage proactive and reactive work at the same time. While this scenario is the most common, it’s also the most likely to increase context switching, burnout, and employee turnover.
1) A hybrid approach rotates the responsibility for addressing ad hoc requests among different members of the analytics and data teams on a weekly basis. This scenario reduces context switching and its associated burnout, and it has the added benefit of giving everyone on the team a broader perspective of what the team is working on.
2) The fully dedicated ad hoc team. Osman often sees this setup in certain industries that receive a non-stop flow of questions, especially in insurance, finance, or anything related to compliance.
Osman highlights the importance of measuring the value of ad hoc work, since today’s ad hoc requests might very easily become part of a company’s product roadmap tomorrow. Soal Data allows companies to identify that tipping point quickly and efficiently.

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Since 2015, over 850 companies have trusted Mammoth Growth to surpass their marketing, product, and business intelligence goals. We offer consulting, integration, and strategic planning services in the following areas:
- Data Engineering / Governance
- BI Reporting & Dashboarding
- Customer Data Platform (CDP)
- Product & Behavioral Analytics
- Lifecycle / Email Marketing
- Modern Data Pipelines
- Multi-Touch Attribution
- Machine Learning
- A/B Testing
Mammoth Growth has deep expertise in a wide range of tools, including Amplitude, Braze, Heap, Mixpanel, Optimizely, Rudderstack, and Segment.
We’re your Growth Team as a Service.