RM Dayton Analytics
Aligning Knowledge Workers in Data Analytics

Technology leaders are often handcuffed by the inability to get the right people to drive their data analytics technology roadmap. They want to leverage the significant technology investments they’ve already made in data analytics, but are hamstringed by traditional talent silos.

This is where RM Dayton Analytics comes in. Headquartered in Plano, TX, RM Dayton builds analytic teams from the ‘inside looking out.’ By first understanding the customer technology stack from the hiring manager’s point of view, RM Dayton puts themselves ‘in the shoes’ of the hiring manager. After interviewing the customer, in which the technology roadmap is reviewed, RM Dayton will align the right people, freeing up the hiring managers for their numerous other responsibilities.

RM Dayton Total Analytic Talent Solutions empowers clients by narrowing the gap between the current state and desired future state of enterprise information management. The right knowledge workers could be anywhere, and they might be a consultant, contingent worker or permanent employee. “Our approach is to view the collective analytic workforce holistically, not subscribing to the doctrine of pre-defined talent silos in aligning analytic knowledge workers,” points out Dayton.

From the day it was founded, the firm has focused exclusively on data analytics. “We are a team building company for data analytics. Our progression has led us to navigate the barriers that exist due to talent silos in data analytics,” extols Robert Dayton, Managing Partner, RM Dayton Analytics.

Grounded in data analytics from experience as practitioners, the company first gains an understanding of the technological roadmap for analytics with its consultative approach. With a laser focus on data analytics, the company stays several steps ahead of broad consulting and staffing firms in aligning analytic talent. RM Dayton aligns knowledge workers in data analytics, including data science, business intelligence, enterprise performance management, data visualization, big data, cloud, predictive analytics, data mining, machine learning, and master data management in a manner that transcends the iterative approach to deployed solutions.

Our approach is to view the collective analytic workforce holistically, not subscribing to the doctrine of pre-defined talent silos in aligning analytic knowledge workers

RM Dayton understands that there is plenty of room to raise the bar over the messy, disconnected traditional approach of sourcing in talent silos. Organizations need an agent that spans the myriad of alternatives and acts in their ultimate best interest in the deployment of top analytic talent. A ‘dot connector’ is needed to match the constantly in-motion matrix of data analytics knowledge workers with the specialized needs of the world’s leading brands. RM Dayton’s connected network becomes their customers’ network in aligning the optimal blend of analytic talent.

For instance, RM Dayton Analytics assisted a global telecommunications company where management driving the project had limited prior success in aligning the right talent to extract the most out of their existing EPM technology investment. They engaged RM Dayton Analytics so that they could leverage the top talent in RM Dayton’s connected network. Upon achieving the business value from their EPM solution that just needed to be brought out, the client not only could combine information in the right slices for each stakeholder, but also could peer into the future with modeling scenarios. The EPM business model also yielded derived analytics via special algorithms, providing prized intellectual capital to executive management. “EPM is the heart and soul of data analytics,” according to Dayton. “If the analytics landscape were viewed as a series of concentric circles, EPM may be viewed as the bull’s-eye – the circle right at the center.”

Moving ahead, the company plans to add refinements to RM Dayton Total Analytic Talent Solutions that drive agility and enhance its customers’ ability to build better teams. “Analytic talent strategies must be holistic, aligning the optimal blend of ‘just-in-time’ analytic knowledge workers when, where and how they are needed,” concludes Dayton.