Home 〉Supply Chain Intelligence 〉Managed Analytics Services 〉Statistical Forecasting as a Service
Home 〉Supply Chain Intelligence 〉Managed Analytics Services 〉Statistical Forecasting as a Service
The creation of the statistical forecast plan remains the critical first step in the planning process. The more rigorous statistical forecasts provide companies with better planning. Even with statistical forecasting, product value, velocity, volume, seasonality, to name a few factors, make the forecasting process uncertain for many organizations. Compounding the problem, few firms have proven able to develop and retain seasoned, and highly skilled forecasters.
What does Chainalytics’ SFaaS do?
SFaaS creates significant value for Chainalytics’ clients. SFaaS provides superior forecasts which serve as the backbone of the planning process. While some understanding of business operations is required to create optimal forecasts, this knowledge is not the critical element for success and is easily obtainable for the client’s business leaders.
Chainalytics’ SFaaS enables companies to leverage outside expertise who are specially trained in handling large volumes of data and the use of statistical methods to develop rigorous forecasts. When a SFaaS provider generates the forecasts, the firm’s business leaders and planners are able to focus on their top priority, running the business.
On a continuous basis, SFaaS helps to:
SFaaS delivery method
SFaaS is delivered using either an “inside the firewall” solution or a secure cloud-hosted solution. Chainalytics’ experts utilize statistical forecasting applications to generate forecasts.
Whether relying solely on internal resources or using an external partner, forecasting remains a critical capability companies can’t afford to get wrong. Chainalytics’ expert forecasting teams have identified methods for improving forecast accuracy from 5% to 30% through investment-grade analytics.
If your company is exploring ways to proactively plan for and strategically design your supply chain for maximum efficiency in sales, production, sourcing, and inventory management through improved forecasting, contact Chainalytics to achieve more with SFaaS.
Chris concurrently serves as Chief Scientist for Chainalytics and the Executive Director of MIT’s Center for Transportation and Logistics. At Chainalytics, Chris pioneered the Freight Market Intelligence Consortium which he presently co-leads.
In his role as Executive Director of the Center for Transportation & Logistics (CTL) at the Massachusetts Institute of Technology, he is responsible for the planning and management of the research, education, and corporate outreach programs for the center to include the Supply Chain Exchange and the Master of Engineering in Logistics (MLOG) graduate program. He is also the founder of the MIT FreightLab – a research initiative that focuses on improving the way freight transportation is designed, procured, and managed. Prior to joining MIT, Chris held senior management positions in supply chain consulting, product development, and professional services at several companies, including Logistics.com, SABRE, and PTCG.
Chris holds a Ph.D. from the Massachusetts Institute of Technology in Transportation and Logistics Systems, a Master of Science in Civil Engineering from the University of Texas at Austin, and a Bachelor of Science in Civil Engineering from the Virginia Military Institute (VMI).
Inam leads the global Freight Market Intelligence Consortium (FMIC) at Chainalytics. In this role, he develops intelligence solutions for the transportation market using machine learning and data visualization techniques. FMIC offers unparalleled visibility to transportation rates and market data across the globe, making it the most powerful and trusted source of freight market intelligence.
Prior to joining Chainalytics, Inam led the engineering team at Transplace, a third party logistics provider, where he developed and innovated such service offerings as network optimization, site selection, procurement, and transportation optimization. These services helped many shippers balance the cost and service trade-offs across their large, complex networks.
Inam holds a Ph.D. from the University of Arkansas in Applied Operations Research, a Master of Science in Industrial Engineering and a Bachelor of Science in Industrial Engineering from Oklahoma State University.