For almost four decades our veteran team has successfully designed and implemented thousands of deployments, spanning a diverse and complex scope of client-objectives.
A national consumer services firm, with millions of customers, had nearly 100 disparate data sources; real-time, daily, weekly, month-end, periodic, leads, referrals, quotes, sales, service tickets, portfolios, productivity, surveys, assessments, new hires and job changes, products and price changes, incentives and spiffs, and more. It took two dozen people all week, every week to prepare and aggregate that data for once-a-week, 3-4 days-delayed, workforce and business unit performance reports.
The Metrics Engine team, collaborating with a performance improvement consulting partners, automated 100% of the entire process to run daily, error-free, in a few hours, with just a single FTE. And, through API-integration with their in-house reporting platform, the client's workforce and management were able to receive daily, instead of late weekly performance reports.
The result was a multiple orders of magnitude improvement in workforce cost-efficiency and performance productivity. And, with daily reporting, sales activity, service satisfaction and customer retention results skyrocketed.
An under-performing regional financial services firm, with hundreds of branches, a typical web presence, and a multi-thousand workforce, had no reliable facts about who their top-performing employees were or who their most valuable customers were: they found out when any of them regularly churned out of the firm.
They were spending heavily on marketing, but had no useful method to know their return on investment and adapt strategy. They requested our assistance to develop pathways to better enterprise intelligence and improved profitability.
Knowing that top employees should be optimizing revenues by directly serving top customers, we devised a three-phased strategy. First, we aggregated all customer/account profiles from multiple disparate core/service systems, calculated Performance Scorecards for each customer, and segmented them by Revenue Contribution, Portfolio Value and Lifetime Potential; by local market and office. We identified the Top 20% of Customers, and which offices and markets were Sales Leaders, Service Leaders or both.
Second, we used the aggregated customer profiles, integrated the active employee lists, and calculated Performance Scorecards for each sales and services individual and office. We segmented them by Revenue and Cost Contributions, Portfolio Value, Attrition Risk, and Retention Opportunity. We identified the Top 20% of Workforce Performers, and which individuals and offices were Sales Leaders or Service Leaders.
A Metrics Engine partner network consulting firm then used these analytics to systemically match, link and assign each of the Top 20% Workforce to each of the Top 20% Customers, by markets, product lines and office; and, automated the internal lead-prioritization and feed functionalities.
The positive results were almost immediate, strong and compelling. Relationship-expansion sales jumped dramatically, both customer Lifetime Revenue Values and workforce Revenue per Employee increased substantially, Top Performer Customer attrition dropped almost completely, Top Performer Employee retention quadrupled, and annualized revenue increased over 30%. Profitability increased further due to improved Top Performer Employee productivity, easier cross-sell/up-sell success and more cost-effective targeted marketing and sales investments.
A national commercial products firms, with a vast range of products and pricing models, needed a fast, reliable and hyper-flexible product recommendation decision and price-quoting engine. Flexibility was mission-critical because many of the cost-factors underlying prices changed daily, sometimes multiple times during each day.
Metrics Engine provided a library of real-time API connectors between their and our systems, configured the necessary algorithms from our native root algorithm library, and enabled the immediate response calculation of product configuration, and item and package pricing. The integration has saved the client millions in development and maintenance costs.
Collaborating with a network of fractional chief financial officers, we're in an ongoing build of a standard API-integration with leading sales engagement, CRM, order-processing, service-ticket, shipping and accounting systems to aggregate disparate source data to calculate KPIs and OKRs for their large network of clients.
Thousands of their clients, who otherwise wouldn't have useful analytics to manage their business, now have the capability to receive a Daily Performance Summary every morning. This near real-time performance management capability has given those clients tremendous visibility on who/what/where of leads, referrals, sales, distribution and service. Revenue growth, cost savings, productivity and efficiency increases, and customer retention have improved in all channels.
Insurance companies design and sell their product and services based on a dynamic range of demographic, geographic, financial and other factors that all impact the potential risk, cost and return on their programs. Actuarial science is the secret behind it.
Metrics Engine has been configured with the most complex structures of cost parameters, rules, filters, qualifiers and more to enable full parametric pricing functionalities for any risk management products and services. The big insurance companies enable this parametric pricing capability for a very limited range of their own products. Metrics Engine widely opens up this power for all products and providers.
A 50-state licensed insurance brokerage began assisting direct-to-consumer businesses in their sale of ancillary insurance and warranty coverages to their core-service customers: travel insurance for individual group members traveling to attend group events, per booking liability protection for home-sharing vacation rental homeowners, property damage coverage, event protection for destination property managers, and more.
Inbound source-data referral and sales transactions were being submitted from over a thousand distribution affiliates across a widely disparate network, in scores of different formats and time-stamps. Because of the myriad of state-by-state insurance rules and approvals, the number of premium-, sales-, referral-, tax- and service-fee paid entities became vast and deep: each insurance transaction spawned dozens of separate micro-transactions requiring strongly-audited tracking, and remittance accounting and management.
Further, the system required the capability to manage and resolve coverage modifications, cancellations, and state-approval-governed premium refunds and commission charge-backs. Finally, the system needed to be the centralized intermediary for multiple back-end claims processing and customer service third-party administrators (TPAs).
Every broker, business, distributor, TPA, property, client, policy and claim needed individual Performance Scorecards, each containing multiple different specific metrics, KPIs, OKRs, and workflow process triggers. These analytics were used to pay commissions, remit compensation and payments, track performance, identify risk hot-spots and provide audit and compliance documentation.
To resolve the high-degree of complexity of the resulting transaction flow, the Metrics Engine team assisted in designing and implementing a comprehensive system-wide transaction management platform that integrated thousands of distribution partners and their sales, scores of state-by-state-approved products, and dozens of insurance carriers, underwriters and their TPAs.
The solution provides tracking and reporting of sales transactions and derived micro-transactions in order to generate insurance sales ‘bordereaux’ reporting to the carriers and underwriters, commission reporting for the sales and referral network, surplus tax reporting and all required premium trust fund accounting.
The system enables the insurance brokerage to maintain primary care and control of data for the purposes of underwriting; evidence of coverage fulfillment; management of customer relationships; first notice of loss, and full administration, accounting, documentation and reporting of all receipts and remittances for all parties.
Revenue per Employee is a common metric to assess enterprise vitality and viability. It can be boosted by increasing revenues and maintaining/reducing the number of employees as you grow. Increased use of automation (e-commerce, subscriptions, process automation, bots, augmented intelligence) to reduce employee headcount is primarily driven by the goal to increase Revenue per Employee and resulting profitability.
While this works best for sales transaction-based businesses, it is more challenging for human-required relationship-based service businesses: many functions cannot be automated and still maintain service quality and customer satisfaction.
We've worked with hundreds of service-oriented relationship-based businesses to design incentive compensation, reward and recognition programs for individual, work-group, team, site/location and market/region performance. This means that individual workforce members earn additional compensation for their individual efforts, and also a percentage share of compensation pools attached to the efforts of the small work-groups, larger teams, locations and larger regions they belong to.
The performance compensation and reward metrics are always based on quantifiable improvements in customer relationship value, service quality, retention and enhancement, referrals, issue resolution, error remediation and other revenue-increasing, cost-reducing and profit-protecting results.
These real 'what-I-actually-do-at-work' performance incentives result in higher retention of top performing employees, natural attrition of under-performing workforce, increases in customer satisfaction and portfolio revenue values, and increased Revenue per Employee.
Working with two competitors in the same market, both with virtually the same history and time in business, vendors, technologies, customer and workforce demographics, market conditions, and parallel financial footprint, gave our team a rare real-world laboratory for what strategies work and which don't in customer profitability and workforce performance.
We recommended to both that they implement Performance Scorecards, with specific metrics and goals, for Customer Relationships, Employees and Business Units (teams, locations, regions, markets/channels and product groups).
Performance Scorecards were suggested because they provide predictive/prescriptive 'leading' and descriptive/diagnostic 'lagging' metric analytics to inform on strategy-execution success or failure. And, typically, these analytics have targets and goals, and are ranked, trended, segmented and drilled-down.
One of our 'laboratory' same-market clients implemented Performance Scorecards with the Metrics Engine platform, the other planned it for the future. Only two months later, the positive results were dramatic. For all metrics, little had changed for the non-Scorecard company, but had shot up steeply for the Scorecard firm.
The positive results were substantial in productivity, revenue and profitability. But, for this client, most impactful was the huge increase in top performing employee retention, longevity, development and advancement (it improved recruiting, too): because it improved customer service, satisfaction and relationship profitability.
A leading merchant services “super-ISO” engaged a Metrics Engine partner network member in the design, development, and implementation of an enterprise-wide performance management initiative, primarily focused on business development, sales, service, and relationship retention and profitability.
With hundreds of thousands of clients, tens of thousands of sales and service reps, hundreds of sales hierarchies, thousands of products, and specialized and varying pricing and fees for every combination thereof, the complexity of integrating multiple data systems and calculating performance metrics was unprecedented.
The Metrics Engine team developed an innovative approach to gather transactional data and calculate real-time and period performance metrics to enable the rapid-velocity-of-change in the organization’s day-to-day sales and service operations, the frequent changes to the organization entity hierarchies, and cost/price changes, contributing to their dramatic growth in the ensuing decade.
A rapidly-growing national email and social-media retail-customer-loyalty SaaS platform engaged the Metrics Engine partner network to assist their rise to the next magnitude of scale and volume. Their platform was strong on outreach capabilities, but limited in scope and capacity on customer loyalty and workforce and distribution system performance management.
The enterprise needed to not only monitor and reward consumers for purchase activities and loyalty, but also client sales and support staff for service quality and satisfaction, and affiliate partners for their referrals and sales.
The Metrics Engine solution generated multiple streams of sales and service performance metrics/analytics and compensation outcomes, transaction-by-transaction, for thousands of locations, tens of thousands of workforce, and millions of consumers. And, comprehensive customer and affiliate analytics enabled a highly-targeted “customer engagement” relationship strategy that improved loyalty levels, revenue per customer, relationship retention, and customer satisfaction, across all categories.
CEO, eCommerce Platform