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TorQEYEA N A L Y T I C S
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Business Analytics – Overview
Analycs is a field of “applied mathemacs to build business soluons”. In addion to it we also
provide cloud plaorm to store data, retrieve data and visualise data in customised forms. The
business soluons provided are built into soware applicaons and the output results are obtained
in real me.
The analycs competencies are
1. Markeng Soluons
→ Customer Life Time (Loyalty Management)
→
Segmentaon
→
Campaign Management
2. Human Resource
→ Recruitment Opmisaon
→ Job Hygiene Management
→ Arion Management
3. Operaons
→
Vendor Management
→ Supply Chain Opmisaon
→ Transportaon Opmisaon
→
Benchmarking and Performance Enhancement
4. Predicve Analycs
→ Real me Forecasng
→ Probabilisc Forecasng
The soluons and applicaons are
→
Dashboard Metrics
→ Business Process Building
→ Cloud Based Interacve Data Base
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1. Markeng Soluons
1.1. Customer Life Time
It captures the business value of a customer in the enre sales process of any company. The value
in monetary terms helps us in markeng and sales spends opmisaons. The segment wise lifeme
value will help us in calculang profitable customer segments and help increase the sales.
Customer Life me Value for one of our brewery Customer
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2. Human Resource Soluons
2.1 Recruitment Opmisaon
Organisaons which hired people who resonate their culture were far more successful than the
organisaons hired people on just competency mapping. The score card creaon on every factors
which include experse, cultural and socio economic factors and personal aribute profiling help
in fing people into organisaonal culture.
We use predicve analycs and cluster factoring to arrive a culture of the organisaon.
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1.2 Segmentaon
The customers are segmented into mulple factors which have direct influence on buying
behaviour. It helps us in determining the actual buying behaviours and its percentage influences.
The socio economic factors like economic mobility are all taken into account and the target
customers are so precise that organisaons just need to help customers buy products rather than
push sales.
Segmentaon for our Brewery Client
1.3 Campaign Management
Targets sales specific data towards high likelihood customers. This helps in increasing upselling and
cross selling maximisaons. Opmised spend in terms of sales per customer and high returns in
terms of revenue per customer.
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2.2 Job Hygiene Management
Producvity always will be lower in an unhealthy work environment. Employees who in general are
not very happy about things around might passively contribute to negave hygiene factors. Once
factors are determined they can be migated and make the overall environment beer. That not
only increases producvity but also the output will be of higher standard. Predicve analycs again
helps us in mapping all the factors and devise management methods to it.
2.3 Arion Management
Ascertaining factors that influence arion overall and specific to task types will help us idenfying
grey areas in organisaons that influence employee resentment. Predicve analycs helps us in
benchmarking and analysing factors mathemacally the impact in varied terms. This helps in
lowering arion and improving employee sasfacon.
3. Operaons
3.1 Vendor Management
Vendors are tough to manage especially when they are spread across large geographies. Vendor
arion is a major issue which impacts business on delivery. Vendor performance is another pain
point for supplier based organisaons. We build in mathemacal models which predict vendor
arion and help in minimising vendor arion and vendor management. Factors ranging from
vendor profitability to vendor socio economic factors are analysed to bring in desired results.
3.2 Supply Chain Opmisaon- Transportaon and Benchmarking
Roung opmisaons in terms of me and cost in a repeve processes and also seasonal process-
es. Breaking down clusters and building efficiency parameters to benchmark with each other.
Reverse logiscs and returns logisc opmisaon. Using mulple logic and algorithms helps us in
building most efficient supply chain system.
Benchmarking also will be extended to producon facilies to improve producve processes.
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4. Predicve Analycs
4.1 Real Time Forecasng
Regression models based on historical parameters in real me helps in forecasng any parameter.
Mulvariate analysis is used for parameters dependent on mulple factors and at a rao relevant.
With dashboard and visual data we could help organisaons to plan for future.
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4.2 Probabilisc Forecasng Instances like risk and fraud is an independent occurrences and has no relaon to one another.
But with probabilisc models we can measure risk and help companies to prepare for any
eventuality using probabilisc models.
Dashboard Metrics
Some of the dashboard and metrics for our clients
Visual dashboards on metrics which maers to businesses will not only help in faster decision
making but also have a compeve advantage in terms of beer products and services.
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Breakdown of the business process and building meaningful metrics and clustering all metrics
helps in micromanagement of businesses even in remote. Appropriate alert systems will make the
system interacve and robust that help organisaons to intervene mely.
PPTS – Dash Board
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