ERP & e-Business Comprehensive Lecture Notes

$9\text{–}10$ case studies uploaded to the learning portal
- Teams choose one to analyse & present, starting “week after next” (exact date TBA)
2 debate topics also available
- Any team may select a debate instead of a normal case study
Deliverables
- Group presentation in the allocated week (slides + Q&A)
- Marks linked to content mastery, critical analysis & class engagement

ERP definition – a single integrated IT system that unifies data, processes and reporting across all departments, providing a “single source of truth.”
Key question posed to class: “Have you implemented / managed / selected an ERP?”
- Majority use $\text{SAP}$ ; others mentioned $\text{Infor}$ , $\text{Microsoft Dynamics}$ , in-house builds, etc.

Implementation times reported: months to multiple years
Complexity isn’t only technical:
- Change-management (culture, processes, people)
- Business-process re-engineering (BPR)
- Cross-functional integration (marketing vs. sales, faculty vs. faculty, etc.)
Vehicle metaphor: modern car = many ECUs. Driver sees only one Check-Engine light → ERP plays the same integrative role.

Technically “just protocols & connectors,” but organisationally:
- Silos with incompatible “languages” (HR, Finance, Engineering …)
- Resistance to change (“nobody likes change”)
- Need for trained change-managers & specialised ERP consultants

$\text{Cost}$ (licence, implementation, TCO)
Past experience / vertical expertise
Post-implementation support & SLAs
Ability to customise (gap → build local solution)
Timeline / deadline adherence
Domain knowledge (e.g.
- “SAP Finance module” experts for banks
- “Dynamics Fashion” consultants for garment firms)

e-Commerce = online merchandise/service transactions (subset)
e-Business = complete end-to-end operation of a business in digital space (superset)
- Includes supply chain, CRM, analytics, HR, etc.

Cultural / localisation issues (Pepsi “brings ancestors back” Chinese fiasco; KFC “eat your fingers off”)
Need for lightning-fast fulfilment & supply alignment
Multi-currency, multi-tax compliance
Trust & security perceptions (customers reluctant to pay online)

Graph:
- $y$ -axis = popularity / sales volume
- $x$ -axis = number of distinct products
Traditional retail (head): few SKUs × huge volume (e.g. Harry Potter 8, $1\text{ book} \times 10{,}000$ copies)
Long-tail e-Business: huge catalogue × low unit sales (e.g. Amazon sells $10{,}000$ niche titles × $1$ copy each)
$\text{Area}<em>{\text{head}} \approx \text{Area}</em>{\text{tail}}$ → revenue parity

Customization (by user) – customer alters product (laptop specs, cake design, BMW $10{,}000$ options)
Personalisation (for user) – system adapts content/offer (AI-driven recommendations)
Example video: Knitten pop-up factory letting shoppers design knitwear live → rapid CAD → print-knit in $20\,\text{min}$ (scarf) to $90\,\text{min}$ (jumper)

Education Features
- Dedicated “Education” pages: 4Cs, videos, blogs, interactive size/clarity sliders
- Virtual appointments & live chat / chatbot
- 360° high-res renders, magnification, AR “hand-view”
- Independent certificates (GIA, IGI) downloadable
Customer Attraction Tactics
- SEO + Google Ads for “engagement rings” keywords
- Social media presence (FB >1.8 M; IG >428 k) incl. influencer collabs
- Massive catalogue, custom-ring builder, birth-stone jewellery
- Seasonal promos, $0\%$ financing, free shipping, store-in-store showrooms
Trust-Building Mechanisms
- $30$ -day money-back guarantee & free return shipping
- Insured, discreet packaging; order tracking
- Conflict-free sourcing pledge; origin traceability
- Lifetime upgrade policy
- Verified reviews, high Trustpilot ratings
- Suggested improvements: region-specific influencers, local certification partners, richer unboxing visuals, Sinhala/Tamil localisation, astrology-based recommender

B2B, B2C, C2B, C2C (traditional labels)
Platform / Marketplace (eBay, Airbnb) → firm supplies matchmaking not inventory
Government-to-Citizen (G2C) portals – fees for digital services
Data-for-Service (Google, Facebook): user pays with behavioural data, not cash ("if it’s free, you’re the product")

Advertising (YouTube pre-rolls, Facebook boosted posts)
Sales / Transaction margin
Subscription (Netflix $\&$ SaaS ERP)
Freemium (baseline free → upsell premium)
- Give $15\,\text{GB}$ Gmail storage, monetise via data & ads
Transaction fees (PayPal, Stripe)
Affiliate / referral (blogs linking to Amazon)

Police report anecdote: 7 visits, manual ledger search, handwritten copies ⇒ highlights need for basic digital record-keeping before AI dreams
Barriers: legacy protocols, lack of political will, culture, underinvestment

Value Proposition
- Instant, legal, high-quality music streaming; massive catalogue; listen song-wise not album-wise
Customer Segments
- Free listeners, premium subscribers, advertisers, emerging artists/labels
Channels: Mobile & web apps, social media, bloggers
Customer Relationships: UI/UX excellence, data-driven recommendations, support
Key Activities: Platform R&D, licensing negotiations, data analytics
Key Resources: Brand, tech talent, servers, algorithm IP, music rights DB
Key Partnerships: Record labels, telcos, investors
Cost Structure: Infrastructure, royalties, salaries, marketing
Revenue Streams: Ad-supported free tier, $\text{Premium subscription}$