We deliver a highly configurable predictive dashboard and guidance apps in five core solutions. Each area is supported by a high-end team and has been proven to deliver better outcomes by industry leaders. Our services include all analytic, integration, and workflow configurations to make the systems work.
Deal odds are often fixed by stage and rarely updated based on actual patterns.
Low participation and completion rates cause data gaps, leading to inaccurate machine learning predictions.
Predictive diagnostic systems score deals and assign odds dynamically based on actual performance.
Personalized guidance system recommends next best actions for deals, recording behaviors and outcomes.
Once algorithms gain more consistency and accuracy, the system seeks to replicate what’s working across all deals to improve performance.
Sales cycle time-to-close is not calculated by most CRM systems.
Weightings are fixed by stage with no true-up to actuals.
People change their behaviors leading to distorted forecasts.
Sales people often hold-back reporting bad news, which means sales forecasts are often overly optimistic.
We provide a scenario based tool that lets sales people see both optimistic and pessimistic scenarios.
Personalized guidance system tracks progress-to-target of each person with personalized deal scenario tools.
OnCorps algorithms learn to optimize deal cycle times, conversion rates, and odds. Decision makers learn the deal scenarios that best meet targets.
Inconsistent behaviors can suppress margins, like applying blanket discounts across all products.
Systems can’t show sales people the pricing scenarios that are working on similar opportunities.
Predictive dashboards identify where pricing can be improved.
Personalized guidance systems nudges changes that optimize margin.
Decision makers learn the pricing scenarios that win at high margin.
OnCorps algorithms learn to optimize supply and demand factors to boost margins.
Most risk systems focus on controls but lack metrics to predict risky behaviors.
Few systems integrate all “lines-of-defense” to identify gaps in risks and control priorities.
Most internal audit groups lack predictive data on internal audit projects time-to-complete.
Predictive diagnostic systems deliver a dashboard to integrate data on changing risks, controls, and behaviors.
Diagnostic systems can cascade down the three “lines of defense”.
Decision makers learn the areas most vulnerable to risk and actions needed.
OnCorps algorithms learn to predict focus areas that result in the most required actions.
Risk thresholds are often fixed, based on historic distributions, leading to higher false positive rates during certain periods.
Anomalies are often addressed in the order received, making it difficult to allocate the right time by risk level.
Predictive systems continuously track recent activity to ensure thresholds are adjusted to truly report anomalies.
Predictive diagnostic systems track time, risk, and experience to optimize oversight.
Personalized guidance systems guide analysts through exceptions based on materiality and learns from their observations.
OnCorps algorithms learn to optimize time by scoring potential errors by risk. Decision makers learn to spend more time on high risk items and less time on low risk ones.
