Business Intelligence (AD-702 (B)) Unit 5 Notes

How unit 5 is examined

This unit applies BI to marketing, sales, supply chain, logistics and pricing; none of the six topics was asked in the supplied papers, so each gets a definition, full-sentence points, an example and an answer frame in case one appears.

Relational marketing

<span style="display:inline-block;padding:.16em .6em;border:1.5px solid currentColor;border-radius:999px;font-size:.68em;font-weight:700;letter-spacing:.06em;text-transform:uppercase;opacity:.75">Not asked since 2022</span>

Definition. <mark>Relational marketing is the strategy of building long-term, profitable relationships with individual customers, using BI on customer data to retain and grow them rather than only to win new ones.</mark>

Key points.

Relational marketing shifts the focus from a single sale to the whole customer relationship, so success is measured by retention and lifetime value, not by one transaction.
Data from the warehouse (purchases, complaints, web visits) is mined to segment customers and to personalise offers, using clustering, classification and association rules.
Retention costs far less than acquisition, so churn prediction models flag customers likely to leave and trigger a retention offer in time.
Loyalty programmes, cross-selling and up-selling raise the revenue earned from each existing customer.
Campaign management tools test a response model on a sample, then send the offer only to customers likely to respond, which cuts wasted spend.
Customer lifetime value is the standard measure: $CLV = \sum_{t=1}^{n} \frac{m_t}{(1+d)^t}$, where $m_t$ is the margin in year $t$ and $d$ is the discount rate.

Example. A customer gives a margin of Rs 1000 a year for 3 years at $d = 10\%$: $CLV = \frac{1000}{1.1} + \frac{1000}{1.21} + \frac{1000}{1.331} = 909.09 + 826.45 + 751.31 =$ Rs 2486.85.

Answer frame. Open with the definition; draw the cycle identify customers, segment, personalise offer, measure retention; develop points 1-6 in order; close with the CLV formula and example.

Salesforce management

Definition. <mark>Salesforce management uses BI models and data to plan, organise, direct and evaluate a company's sales team, covering forecasts, territories, quotas and performance.</mark>

Key points.

Sales analytics forecasts demand from past sales, so quotas and targets are set on data and not on guesswork.
Territory design divides customers and regions among salespeople so that workload and sales potential are balanced.
Sales force automation (SFA) records leads, visits, quotations and orders in one system, giving management a live sales pipeline view.
Lead scoring ranks prospects by their chance of buying, so salespeople spend time on the best leads first.
Compensation and incentive plans are tied to measured results, which keeps effort aligned with company goals.
Performance is judged by KPIs such as conversion rate, revenue per salesperson and quota attainment.

Formula. $\text{Quota attainment} = \frac{\text{actual sales}}{\text{quota}} \times 100$.

Example. Actual sales of Rs 45 lakh against a quota of Rs 50 lakh give $\frac{45}{50} \times 100 =$ 90%.

Answer frame. Open with the definition; list the activities forecast, territory, quota, SFA, incentive, evaluation; develop points 1-6 in order; close with KPIs and the quota attainment example.

Business case studies

Definition. <mark>A BI business case study describes a real organisation's problem, the BI technique applied and the measured benefit, so that the lesson can be reused elsewhere.</mark>

Key points.

Retail: market basket analysis with association rules (bread implies butter) decides shelf layout, bundles and promotions, and lifts sales per visit.
Banking: classification models score loan applicants for credit risk, which lowers defaults and speeds approval.
Telecom: churn prediction on call and billing data lets the firm target at-risk subscribers with retention offers.
Airlines and hotels: revenue management forecasts demand and changes fares and room rates dynamically.
Manufacturing and logistics: supply chain analytics cuts inventory, transport cost and late deliveries.
Each case follows the same pattern: business problem, data used, BI method, result in numbers, and lesson learned.

Answer frame. Open by defining a case study; pick two or three sectors from the points, and for each write problem, technique, benefit; close with the common pattern in point 6.

Supply chain optimization

Definition. <mark>Supply chain optimization uses BI and mathematical models to run the flow of goods, information and money from suppliers to customers at minimum total cost while meeting the required service level.</mark>

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Key points.

The chain links suppliers, manufacturers, warehouses, distributors, retailers and customers, and BI gives one view of all of them.
Strategic decisions fix plant and warehouse locations, tactical decisions set production and inventory plans, and operational decisions schedule orders and routes.
Demand forecasting drives every other plan, and better forecasts reduce the bullwhip effect, where small demand changes grow larger up the chain.
Inventory control balances ordering cost against holding cost, using the economic order quantity.
Supplier selection and performance dashboards track lead time, fill rate and on-time delivery.
The goals are lower cost, lower inventory and better delivery service.

Formula. $EOQ = \sqrt{\frac{2DS}{H}}$, with $D$ annual demand, $S$ ordering cost per order and $H$ holding cost per unit per year.

Example. $D = 1200$, $S = 50$, $H = 6$: $EOQ = \sqrt{\frac{2 \times 1200 \times 50}{6}} = \sqrt{20000} =$ 141 units (about 8.5 orders a year).

Answer frame. Open with the definition; draw the chain diagram; develop points 1-6 in order; close with EOQ and its example.

Optimization models for logistics planning

Definition. <mark>Optimization models for logistics planning are mathematical models that choose the values of decision variables to minimise cost or maximise service, subject to constraints such as capacity and demand.</mark>

Key points.

Every model has three parts: decision variables (quantities to ship), an objective function (total cost) and constraints (supply and demand limits).
The transportation problem, $\min \sum_i \sum_j c_{ij}x_{ij}$, uses linear programming to ship from sources to destinations at least cost.
The assignment model matches tasks to resources one to one at minimum total cost.
Network models find the shortest path and plan vehicle routes to cut distance and delivery time.
Integer and mixed-integer programming choose facility locations, where the answer is open or closed, not a fraction.
Simulation and what-if scenarios test a plan against uncertain demand before it is adopted.

Formula. Transportation constraints: $\sum_j x_{ij} \le s_i$ (supply of source $i$) and $\sum_i x_{ij} \ge d_j$ (demand of destination $j$), with $x_{ij} \ge 0$.

Example. Two plants with supply 30 and 20 serve two towns with demand 25 each; sending 25 from plant 1 to town 1 and 5 to town 2, and 20 from plant 2 to town 2, uses all supply and meets all demand.

Answer frame. Open with the definition; write the three parts of a model; develop points 2-6 with one line each; close with the transportation formula and the example.

Revenue management system

Definition. <mark>A revenue management system uses demand forecasting and optimisation to sell the right product to the right customer at the right time and price, maximising revenue from fixed, perishable capacity.</mark>

Key points.

It suits airlines, hotels and car rental, where capacity is fixed and an unsold seat or room earns nothing after the departure or night has passed.
Customers are segmented by willingness to pay, and fare classes or dynamic prices are set so each segment pays a different amount.
Demand forecasting by date, season and event supplies the input for every pricing and allocation decision.
Capacity allocation reserves seats for late, high-paying customers instead of selling all early at low fares.
Overbooking covers no-shows, with the risk of denied boarding balanced against the cost of an empty seat.
Results are tracked by yield and occupancy metrics and fed back to improve the forecast.

Formula. $RevPAR = \frac{\text{room revenue}}{\text{available rooms}}$, and airline revenue $= \text{load factor} \times \text{average fare} \times \text{seats}$.

Example. A hotel earns Rs 60,000 room revenue from 150 available rooms: $RevPAR = \frac{60000}{150} =$ Rs 400.

Answer frame. Open with the definition; explain perishable capacity first; develop points 2-6 in order; close with RevPAR and the hotel example.

Last-minute revision

Relational marketing builds long-term customer relationships; retention is cheaper than acquisition.
$CLV = \sum m_t/(1+d)^t$; Rs 1000 for 3 years at 10% gives Rs 2486.85.
Salesforce management covers forecasting, quotas, territories, SFA and incentives.
Quota attainment is actual sales divided by quota, times 100.
Case studies: retail basket analysis, bank credit scoring, telecom churn, airline pricing.
Supply chain optimization minimises total cost at a set service level.
The chain runs supplier, manufacturer, warehouse, distributor, customer.
$EOQ = \sqrt{2DS/H}$; D 1200, S 50, H 6 gives about 141 units.
Every optimization model has variables, an objective and constraints.
The transportation problem minimises shipping cost by linear programming.
Revenue management sells perishable fixed capacity at the right price to the right segment.

Memory hooks

Relational marketing: keep the customer, not only catch one.
Salesforce: forecast, quota, territory, track.
Supply chain flow: S-M-W-D-C, supplier to customer.
Optimization model: V-O-C, variables, objective, constraints.
Revenue management: "perishable seat, dynamic price".

Coverage checklist

Relational marketing: no past questions; definition, CLV formula and example covered.
Salesforce management: no past questions; territory, SFA, quota attainment covered.
Business case studies: no past questions; retail, banking, telecom, airline, manufacturing covered.
Supply chain optimization: no past questions; diagram, EOQ and example covered.
Optimization models for logistics planning: no past questions; transportation model covered.
Revenue management system: no past questions; RevPAR and overbooking covered.

Account

Business Intelligence (AD-702 (B)) - Unit 5 Short Notes

How unit 5 is examined

Relational marketing

Salesforce management

Business case studies

Supply chain optimization

Optimization models for logistics planning

Revenue management system

Last-minute revision

Memory hooks

Coverage checklist