- 509-850-0406
- office@pmally.com
- Seattle - Chicago - New York
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Founded in 2014, PM Ally is driven by a strong belief that organizations striving to make data-driven decisions often find themselves lost in the vast landscape of data, technology, and analytics solutions available today.
Our goal is clear: to guide organizations toward success fueled by insights. We offer end-to-end data and analytics expertise, employing a resource-efficient, people-centric, and consultative approach.
Our analytics capabilities empower companies to enhance profitability by infusing scientific decision-making into sales and marketing efforts. Unlike most analytics firms, we serve as a comprehensive one-stop shop for all things data and analytics. Our unique differentiator lies in our people-first, business-centric approach.
Our company culture thrives on continuous learning and growth. Thanks to our team’s unwavering commitment, PM Ally has achieved accelerated year-over-year growth.
At our data analysis and digital transformation business, we don’t just offer services; we deliver transformative solutions tailored to your unique needs. Our team of experts combines cutting-edge technology with deep industry insights to drive innovation and efficiency. We pride ourselves on our customer-centric approach, ensuring personalized support and measurable results. Choose us to stay ahead of the curve and unlock your business’s full potential with data-driven strategies that outpace the competition.
The rate is dependent on the individual situation of the organization. However, on average, we are able to save organizations 28% of labor cost.
Infrastructure of each organization is very unique. Some organizations are very technology dependent. This where we see the majority of optimizations, either by replacing manual processing with emerging tech or moving on-prem servers to cloud. On average, we are able to optimize the infrastructure by 32%.
This refers to the collection of raw data from both internal and external sources. The first phase of data collection involves identifying what data to collect and then establishing a process to do so (i.e. conducting a survey or retrieving automated IoT data). Decisions made here will affect the quality and usability of data throughout its life-cycle.
The final step of the process is the application of data analytics processes to solve real-world problems and, in a business setting, increase revenue. This can be done by either using data analytics to optimize the efficiency internal operations and decrease overhead costs or by using data-driven insights to identify and exploit new revenue streams.