A presentable story for stakeholders to drive results.
Qerent has one simple purpose: To amplify your business’s performance by taking you through the journey of what has changed in your business, why and what you should do about it.
Qerent is a performance diagnostics solution with industry-specific visual components, embedded contextual data analytics and automated data storytelling.
Qerent establishes causality and offers greater insight, surpassing traditional business intelligence (BI) solutions, delivering the insights you need to make better, proactive, targeted decisions.
Qerent is not only a solution to the questions that Business Intelligence struggles to address but does so in an automated fashion to reveal causality, providing you with contextual insights when telling your business story.
Qerent goes further than traditional Business Intelligence (BI) by exposing the story of what happened in your business, why it happened and what to do about it.
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TOP BRANDS, GLOBALLY
For the past 20 years, BSC has mastered the application of analytics and smart technology to increase business performance.
Copper Mining and Processing
Planning Science
Integrated Business Planning
An Integrated Business Planning model combining operational drivers across the Copper mining and processing value streams with site- and macro-level financial drivers to yield a financial forecast and . This allowed for production planning, bottleneck analysis and studies on business case and capital investment profitability.
Banking
Planning Science
Rolling Forecast
This solution provided the bank with an intimate understanding of their key drivers of financial performance and the impact a change on any of these key drivers would have on their future through comprehensive scenario planning. It then used this information to ensure the bank would remain compliant and continue to adhere to regulations in an ever-changing environment.
Multi-commodity Mining Group
Planning Science
Group Integrated Planning
A fully integrated model including stochastic analysis, that provides an understanding of group risk exposure by using the variability in key drivers to calculate a confidence in achieving the Business Plan at Business Unit and Group level. This facilitated meaningful communication to shareholders and market analysts, providing assurance of the likelihood of meeting targets and exposure to key risks.
Media
Planning Science
Rolling Forecast
Developed a rolling forecast model that allowed the Financial Planning and Analysis team to report a monthly rolling forecast for the group, perform Budget vs Actual analysis, evaluate and quantify the causes of deviations, create multiple scenarios to stress test plans and generate amended Budgets for approval.
Planning Science
Platinum Mining and Processing
Strategic Portfolio Planning
A portfolio optimisation solution that modelled the production and economics of a portfolio of mining assets and the processing value chain, from mine to market, for a major Platinum operator. This provided an enhanced decision support capability through rapid scenario generation by allowing flexing of underlying operational driver, commercial contracts and macro-economics.
Planning Science
Utilities
Capital Portfolio Optimisation
A capital allocation decision support solution was built to allow for capital projects across different business units to objectively compete for capital based on liquidity and operational constraints. An optimization simulation provided the top portfolio configurations given the strategic focus criteria.
Commodity Market
Planning Science
Commodity Supply Demand Modelling
Cost models that estimate historical and forecasted future production, cost, and emissions data for all the major assets in the world for a given commodity. This allows clients to analyze market supply, demand, pricing and make asset valuations.
Extraction
Productivity Science
Load and Haul Traffic Orchestration
Derived and tested the impact of orchestrating haul truck traffic within open-pit mine operations. Productivity inefficiencies due to congestion were identified and strategies to address them were simulated resulting in double-digit percentage increases in throughput.
Processing
Productivity Science
In-Shift Production Optimisation
Developed and deployed a solution for a gold miner to use to optimise gold production in the event of unplanned stoppages in the plant. The tool utilises real-time data to determine the optimal set points to run the plant at, factoring in the various operational and metallurgical constraints.
Processing
Productivity Science
Plant Design Validation
Configured a model to dynamically simulate the flow of material, in detail, through the modules for a new lithium plant. The model was designed to identify any systemic issues within the plant layout, specifically within the realm of buffer sizing and equipment utilisation.
Logistics
Productivity Science
Working Capital Prediction Model
Configured a model to dynamically simulate the flow of concentrate from the client’s mines in Western Australia, through to the processing plants in China factoring in the multiple modes of transport along the way. The model determined the working capital requirements across the value chain.
Mining
Productivity Science
Tactical Planning Models
Developed a set of value stream and value driver tree models for various mines for a mining client. These models were designed to identify system bottlenecks, determine system throughput, and test various ‘What-if’ scenarios as part of the business improvement processes for the client.
Logistics
Productivity Science
Integrated Planning Logistics Model
Implemented a predictive simulation model that determined the logistics requirements for a copper smelter every week. The simulation integrated production plans and maintenance schedules at the smelter with arrival and departure times for the vessels at the port to work out the road and rail logistics requirements.
Revenue Science
Telecoms
Telcosurance Personalisation
Using subscriber behavioral and transactional data, prepaid customers were segmented, and targeted with different insurance offerings based on the highest probability of conversion. Additionally, usage data helped optimize contactability rates and drive better conversions.
Revenue Science
Telecoms
Channel Incentive Structure Modelling
Introduced a Smart Commissions framework to address prepaid rotational churn supported by a commercial model to simulate different incentive structures for channel partners. Commissions inefficiencies were resolved through redefined performance measures & targets, which resulted in a decrease in churn.
Healthcare
Revenue Science
Revenue Forecasting & Diagnostics
A mathematical driver-based model of the finance process was built. This allowed for improved forecasts through driver-based machine-learning & diagnostics by tracking shifts in drivers & quantifying the resultant impact, for proactive interventions across hospitals, funders, disciplines and doctors.
Healthcare
Revenue Science
Outbreak Detection and Alerting
Improve the ability to promptly detect outbreaks by providing the infection control teams with an automated outbreak detection solution for hospitals and wards, while also providing a better understanding of the leading contributors to infectious outbreaks.
Retail
Revenue Science
Stock-out Prediction Models
Machine-learning forecast to provide retailer with weekly product predictions across relevant SKU’s reducing the probability of stock-outs. The end-to-end process of data sourcing, integration, processing, model training & deployment into a production environment, serves 10 000 stores
FMCG
Revenue Science
Early Warning Prediction System
Effective and swift responses to competitor promotional activity by identifying anomalous transactional behaviour in sales volumes, pricing & emerging SKUs at a localised level. Automated reports are distributed to operational teams to proactively combat high risk competitor activity.
Revenue Science
Customer Segmentation & Lifecycle Management
Detailed segmentation modelling to support lifecycle management, hyper-personalization and loyalty. Using the segment profiles and attributes, detailed engagement strategies were formulated and executed.
Revenue Science
Product Recommendation Engine
Simulating, forecasting & re-rating subscriber spend and usage behavior over 24 months to proactively recommend appropriate tariffs at contract renewal stage.
Revenue Science
Launch of Enterprise Product Portfolio
Helped launch a portfolio of enterprise tariffs targeted at different customer segments and verticals. This included commercial modelling, forecasting & simulation to determine optimal pricing & proposition design, to drive adoption and mitigate cannibalization from existing consumer offerings.
Revenue Science
Lead Allocation & Conversion Optimization Engine
Profiled and scored incoming calls to determine the optimal agent profile to service the lead who would have a higher likelihood to improve closing rates and overall effectiveness.
Revenue Science
Customer Insights, Modelling & Reporting
Consolidated data sources, cleaned and enriched data fields with text mining algorithms. The data was then profiled and statistically analysed to extract key insights and trends on acquisition, churn, product affinity and market penetration
Revenue Science
SALESFORCE OPTIMISATION
Developed a dynamic visit allocation solution, which prioritises visits based on localised needs of customers across a variety of strategic KPI’s. Subsequently created a route scheduling optimization model to minimize travel duration and visit days and provide weekly visit schedules to the salesforce.
Revenue Science
Product Pricing & Proposition
Pricing analytics and commercial modelling to develop two innovative propositions for Standard Bank Retail including proposition design, customer testing / validation and reporting.
Revenue Science
Segmentation & Embedded App Analytics
Blend digital banking behaviour with transactional and customer information to improve customer engagement within the digital mobile banking application.
Revenue Science
Consumer Product & Services Chatbot
A customer-facing concierge chatbot on homepage, aimed at assisting users to find the information they are looking for as quickly as possible. The solution aims to improve conversion by reducing drop-off of potential customers.
Revenue Science
Collections Optimization Engine
Built a collections optimization engine using machine learning to predict the likelihood of collection for a set amount on a specific date whilst minimizing collection costs.