Glimpse delivers real-time data analytics solutions that leverage our industry expertise, quantitative analytics, machine learning, real-time data connections, and accessible what-if analysis tools
Glimpse makes answers happen now.
Leaders who want to ask a few basic questions can no longer afford to schedule subsequent meetings just to allow analysts time to perform tedious queries, joins, and data cleanups to answer a few basic what-if questions.
Glimpse provides access to real-time information based on data consolidated from across all enterprise systems.
Glimpse transforms that data into a common format, aligns and translates date, time, and currency data, and presents the facts you need for immediate what-if analysis.
Glimpse solutions are delivered in Power BI or Tableau, depending on our client’s requirements.
What We Do
Data and Analytics
We configure Glimpse dashboards to provide instant access to real-time data consolidated from many systems that span the client’s enterprise. Data transformation is done nearly instantaneously in a cloud service. The analytics presented are always up to date. Predictive analytics offer a what’s next view of sales, production, or supply chain traffic. Prescriptive analytics guide actions that will enable cost reductions and greater productivity.
Custom Modeling and Solutions
We work closely with client organizations to develop customized models and solutions that enable our clients to enjoy and benefit from the experience of experimenting with a “digital twin” of their production operations. Our custom solutions can provide highly specialized real-time reports and analyses, such as economic order quantity calculations, truck dock utilization plans, or contact center staffing plans and forecasts. In addition, What-if support is built into many of our custom solutions to enable discussion of alternative approaches in team meetings without waiting for analysts to gather further data.
Machine Learning Solutions
Glimpse dashboards can employ advanced machine learning algorithms to recognize patterns, make complex assignments, or build highly reliable forecasts from historical data available. Models run in real-time and have many practical applications, like shopping cart fraud detection, setting of credit policies for individual customers, and identifying customer’s most likely subsequent purchases. Machine learning models are handy for such diverse tasks as allocating marketing spend to maximize sales leads or choosing process parameters and ingredients to maximize yield from a batch process.
Quality Focused, Result Driven
Marketing Leads Pipeline Analysis
Monitor marketing channel lead generation performance to optimize marketing spending and inside sales performance.
Integrate sales and product performance across multiple ERP systems.
Multi-Echelon Supply Chain Cost Reduction
Optimize transshipments and inventory ordering to minimize the total cost for a network of distribution centers.
Supply Chain Disruption Recovery Planning
Identify likely disruptions and impacts from supplier outages. Plan replacement products and identify alternative suppliers.