BCS Methodology

Our approach follows a systematic 7-step process:

1. Defining the Problem

We start with the big question - improving customer service. Together with clients, we define specific areas of improvement in their customer journey, always considering their values and brand promise.

2. Collection of Data

We identify available data sources including property descriptions, manuals, summaries, itineraries, customer reviews, prices, timings, and other relevant training data. We also consider technical and regulatory restrictions that define the framework for data collection and analysis.

For example: 'For the BCS-A Tester included into our presentation for Omena Hotels (Finland), we have gathered data available on their website, their application, and their expedia entries. This included descriptions of rooms and amenities, booking process, history of the Omena Hotels, and links to partners' site.'

3. Cleaning and Preparing the Data

Data preparation involves removing errors, filling missing information, and formatting data correctly for AI understanding.

For example: 'While preparing data for the BCS-A Tester included into our presentation for SOKOS Hotels (Finland), we reorganised, structured, and edited information gathered from SOKOS Hotels website, creating a separate file that AI Assistant can understand and work with.'

4. Building a Model

We choose the right algorithm and build the AI model that learns from client data, identifying patterns for predictions and decisions.

For example: 'Both for Omena and SOKOS Hotels we tested different LLMs, such as Gemini, Claude Haiku, Claude Sonnet, and GPT and chose Claude Sonnet.'

5. Testing of the Model

Rigorous testing on new data, with adjustments and fine-tuning as needed.

For example: 'The B CS-A Tester included into our presentation for SOKOS Hotels (Finland) we tested by providing for the chosen LLM, Claude Sonnet, the data related to SOKOS Hotels we have collected and prepared. The testing consisted of asking various questions in a number of languages, and checking the answers against the data input.'

6. Deploying the Model

Implementation in real-world applications - customer-facing apps, internal tools, or automated processes.

7. Monitoring and Improving

Ongoing performance monitoring, updates with new data, and continuous improvement.

Our Integrated Service Approach

AI Assessment (Foundation Phase):

Goals, challenges, and capabilities analysis
Prioritised AI opportunities (ranked by benefits, cost, implementation ease)
Organisational readiness review
Data and tool assessment
ROI projections

AI Transformation Consultancy (Execution Phase):

8 comprehensive components:

1. Objective setting

2. Project planning and budgeting

3. Securing required resources (people, data, tools)

4. Project management

5. Stakeholder communication

6. Process and job description updates

7. Vendor and SLA management

8. Training and documentation

This integrated methodology ensures seamless progression from strategic planning through successful BCS-A implementation, maintaining focus on luxury sector customer service enhancement throughout.