Fusionex and Alliance Islamic Bank Sign MoU to Accelerate Halal SME Growth
A memorandum of understanding aimed at giving halal sector small businesses the digital tools and financing visibility usually reserved for large corporates.
Read the storyClient work
A logistics group replaced fragmented service records with a single customer view, and cut the time it took to answer a simple question.
In May 2020, Fusionex announced a customer experience project with the Nationwide group of companies, a Malaysian logistics and courier business. The work addressed a problem familiar to almost every established service company: customer information had accumulated in several systems that did not talk to each other.
Logistics businesses grow by adding services. Each addition tends to arrive with its own operational system, and each system keeps its own record of the customer. Over time the same client exists several times over, in slightly different forms, across booking, tracking, billing and support.
The operational consequence appears at the service desk. A customer asking a simple question about a delayed shipment triggers a search across systems that do not share a common identifier. The answer eventually arrives, assembled by hand, several minutes later. Multiply that by thousands of enquiries and the cost is substantial, and the customer experience is worse than the underlying service quality deserves.
The work centred on consolidating those fragmented records into a single view of the customer, so that a service agent could see the full relationship, including current shipments, history and open issues, without moving between applications.
A unified view changes what else becomes possible. Once records are consistent, the same data supports pattern analysis: which routes generate the most enquiries, which service failures precede a customer leaving, which accounts are quietly reducing volume. That analysis is impossible while the underlying records disagree with each other.
Data consolidation attracts none of the attention that artificial intelligence does, and it determines whether the interesting work is possible at all. A forecasting model trained on inconsistent customer records produces confident and useless output. The unglamorous work of reconciling identity across systems is the precondition for everything that follows.
It is also where enterprise software actually earns its reputation. A company that delivers a clean single customer view for a mid sized logistics group is demonstrating something more relevant to most buyers than a benchmark score.
The project belongs to the company's core enterprise practice rather than to the platform work that dominated the rest of 2020. It is included here because that core practice, unspectacular and repeatable, funded the more visible projects and represents the majority of what the company did over fifteen years.
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Read the storyStory questions
The May 2020 project consolidated customer records that had accumulated across separate operational systems into a single unified customer view, so service staff could see a complete relationship without switching between applications.
Growth usually means adding services, and each new service tends to arrive with its own operational system holding its own version of the customer record. Over time the same customer exists several times in slightly different forms.
Predictive models trained on inconsistent records produce confident but unreliable output. Reconciling customer identity across systems is a precondition for any dependable analysis built on top of it.