Small Business Data Analytics Case Study | BrewByte Café

BrewByte Café is a small local café in Bandar Seri Begawan that sells coffee, pastries, and light meals. Although the café is small, it wants to improve daily operations by understanding sales patterns, customer preferences, and inventory usage.

The café collects simple data from several sources, such as:

• Daily sales records from the POS
• Weekly inventory usage logs
• Basic data on operating costs (ingredients, utilities, supplies)

By analyzing these datasets, BrewByte Café hopes to improve menu planning, schedule staff more efficiently, reduce wasted ingredients, and offer better customer service. 

As small businesses in Brunei increasingly adopt digital tools, BrewByte Café wants to move from manual record-keeping to a more data-driven system, allowing faster and smarter decision-making.

Role

You are currently working att BrewByte Café, assisting the small business with improving its data workflows. Over the past three months, you have been helping organize daily sales sheets, reviewing feedback trends, and identifying issues in how data is recorded and reported.

Your manager has now asked you to prepare a presentation and summary sheet for the café owner and potential partners. Your goal is to show how integrating multiple small datasets can:

• Improve menu and pricing decisions
• Optimize inventory purchases
• Track daily revenue and cost performance

If your presentation is successful, you will be given a project to design a dashboard system that BrewByte Café can use daily to monitor sales and operations.

The café uses several simple data sources to guide decision making, such as:

• POS daily sales reports
• Supplier records
• Weekly inventory usage sheets
• Daily cost and expense records

BrewByte Café’s long-term goal is to move toward a more data-driven management style—improving menu planning, optimizing supply purchases, reducing waste, and better understanding customer behaviour. The café wanted to understand :

• Which items were the most profitable
• How long does ordered item arrive from ordered date
• Which items consistently ran low
• Which suppliers has the most profitable item

A combination of sales records, customer feedback, and inventory logs to identify key operational issues.

If the project were to be successful, how would BrewByte achieve the below:

• Introduced new bundle sets based on top-selling combinations
• Adjusted inventory purchases to match demand
• Improved staff scheduling during peak hours
• Added QR-code customer feedback prompts to gather faster insights

Assignment Activity And Guidance

Activity 1

You can decide on the industry and context of your previous client project(s), but it is advised that you reflect on the vocational scenario and give examples or evidence of how they used data and information generated from local/national datastores to support business processes. Example(s) can be something you have thought of yourself or from a real business case.

1. Presentation

Your presentation should address the following areas.

a) Discussion on how data and information support business processes, including the value they have for organizations

b) Discussion of how data is generated and used by organizations to support business processes and the tools for manipulation to form meaningful data

c) Your assessment on the impact and value of data and information, in relation to previous client project(s) for real-world business processes in practice

d) An overview of human- and machine-generated data mechanisms and tools that could be used as part of process to manipulate and form meaningful data.

2. Summary Sheet

The summary sheet will accompany the presentation to include the following.

• Detailed description of common threats to data and how they can be mitigated at personal and organisation level
• Discussion of the social, legal, and ethical implications of using data and information to support business processes, recognising relevant regulatory issues
• Analysis based on one of your previous client project(s), on the impact of using data and information to support business real-world processes
• Evaluation on wider implications of using data and information to support business processes, including failure to adequately protect data and information.

Activity 2

From the selected organization in Task 1, explore solutions driven by data for improving their decision making.

As part of your tasks, you are expected to:

• Provide a discussion of how data science associated tools and technologies, support business processes and inform decision making.
• Present your design of a data science solution to support decision making in relation to real-world problems faced by the organization, assessing the benefits of using data to solve problems in practice.
• Summarize implementation of a data science solution with the organization, making clear how design performed a specific task to support problem solving or decision making.

Justify recommendations that support decision making in reference to your real-world problem and conclude your case study with an evaluation on the use of data science techniques, addressing how these met the organization’s user and business requirements.

Expert Answers on Above Data Analytics Case Study

How data and information support business processes

Data help businesses in making informed decisions based on evidence. In the given case analysis of BrewByte Cafe, with the help of data on sales, inventory and cost, the company can easily improve its menu planning, control expenses and achieve reduction in the waste.

How data is generated, used and transformed

There are different sources of data in the given case scenario which includes POS systems used in the sales process, supplier invoices, inventory data and expensive records. This data can be utilised in a meaningful way to make informed decisions like promoting the best selling items, infusing more items that generate profit etc.

Impact and value of data

The value of data is significant as in the given case scenario of BrewByte Cafe, the analysis of sales and inventory data indicated the top selling items, and as a result it can be possible to make better inventory planning, and undertake improved pricing decisions that can help business grow.

Human and machine generated data

Data generated from customer feedback, manual inventory check and staff record are considered as human generated data whereas the machine generated data includes POS sales reports, digital transaction logs etc.

Common threats to data and mitigation

The threats are mainly applicable in the form of loss of data, error on the part of humans. Unauthorised access or it can be from cyber attacks. Strong mitigation system through password protection, backups and staff training can be utilised to address the issue.

Social, legal and ethical implication

There are social, legal as well as ethical implications from data usage in the form of customer privacy, data accuracy and consent. It is important to comply with appropriate data management laws to avoid any kind of misuse of data.

Impact of data in real world processes

Data helps in improving transparency, efficiency and accountability in business operations and case companies like BrewByte Cafe can utilise data in supporting its business decisions such as purchasing or inventory management.

Failure from protection of data

The failure in the protection of data can result in reputational damage, legal penalties and financial losses.

How data science tools support decision making

There is a significant role of data science tools in supporting the decision making process. Tools like dashboards, visual analytics and trend analysis are useful for businesses in forecasting demand, identifying patterns and monitoring performance thereby allowing for faster and more accurate decisions.

Design of a data science solution

By designing a dashboard that takes into account the inventory, sales and cost data, it can be possible to keep a track on revenue, stock levels and supplier performance which ultimately helps in overstocking or understocking and help businesses achieve operational efficiency.

Implementation summary

Data collected through POS and inventory logs are visualised in the dashboard which allows the manager to monitor performance on a real time basis and thereby taking quick decisions in solving operational related problems.

Justification and evaluation

This data driven approach is quite effective in improving efficiency, reducing waste and supporting the managerial decisions. It is therefore highly justified in the case of BrewByte Cafe in its target of becoming a data driven business.

This model answer is reviewed by Laura Bennett, Management Expert from University of Bristol, specialises in management case study writing and analysis. Disclaimer: This answer is a model for study and reference purposes only. Use it for your learning to do your assignment on your own. Please do not submit it as your own work.

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