Macroeconomic (Covid) forces leading to parts & labor shortages, industry dynamic (insufficient manufacturing capacity on-demand), and lack of service-oriented culture constrained by a poor technology platform for delivering end-to-end services management have resulted in lost opportunities for manufacturers.
Manufacturers vs. Channel Brands
Repair Generalists vs. Specialists
Large Internet Chains vs. Local Garages
Importance of Services-oriented Culture
The Aftermarket business brings double-digit operating margins for sure, but still is the most evasive and overlooked sector of the manufacturing economy. Delivering quality service at the right price point is an art and a science. Customer loyalty means you will need to predict the failure point and ensure you meet a high level of service (SLA). Simply put, a Single Version of the Truth (SVOT) is the first step to Customer Service Management (we coined CSM).
CBC consults on Services Supply Chain and delivers a rich platform of business services. Powered by AI/ML and Cognitive (data science and data engineering) tools, we’ll help you retain your customers.
Maintenance has seen its north-star moment. From Corrective (identifying and correcting an issue) to Preventive (routine checking for anomalies), to Perfective (improving performance through maintainability); we now enter a world of cognition, Adaptive (maintaining in a changing environment that’s data-driven instead of rules or routine-based) maintenance.
Adaptive (or Condition-based) Maintenance is feasible in many industries that can harvest machine data including the external environments that they provide services in. The data is then curated and ingested into data science models to gain predictive and prescriptive analytics such as the probability of failure, detection of an anomaly, and predicting when repairs are needed to save work stoppages.
AI-based Field Services Management (FSM) is an offshoot of Predictive Maintenance methods. Only in FSM, it is all about improving the efficiency of Technicians in the field.
The framework we use at CBC manages Fault Location Classification, Recommendations based on Machine Learning (ML Ops), and a Technician Dashboard that helps visualize fault and spare parts accurately.
We implement FSM on any of the hyper-scalers to curate chat data, dispatch data, CPE performance, line performance, outage data, weather data along with external data from prediction repositories. Searching for parts based on images and improved PIM (product information) are key tenets of FSM solutions including training for Technicians.
The business need for fleets or large assets management is based on two key factors. Improve utilization and Reduce downtime of assets.
CBC approaches this problem two-pronged.
First, we use data science models to predict the failure probability at a part-level and smoothen the results for false positives. Second, we use advanced Optimization techniques to preemptively schedule the fleet for maintenance (preventive and corrective) in the busy garages automatically.
Our solutions are used in a variety of industries where productivity gains have been commonplace alongside the high availability of assets for production purposes.
AI apps for Sustainability and Mobility are a growing space for Enterprise solutions. From proactive alerting to notifications at a process-level being served to the workforce in the field or at any place they call “workplace”.
The pandemic era has furthered the importance of a diversified workplace where employees need to access their operations information and/or service their Customers offline. Mobility is a central part of IT strategy for many organizations.
CBC understands the need for transformation alongside the compliance and privacy considerations that go hand-in-hand with enterprise mobility. Our labs constantly research new and upcoming trends to ensure our Customers have the best.