Data Analytics

Data is an essential element of modern business. Today, with the massive amount of data being generated, analyzing and utilizing it is directly linked to gaining and maintaining a competitive advantage. Companies are required to predict market trends, understand customer needs, and improve business efficiency through data analytics. Even in an uncertain business environment, data-based decision-making provides a solid guideline and is an important strategy that supports sustainable growth. By maximizing the power of data, companies can pave the way to the future.

Our Essential

We provide comprehensive support for data-based strategic decision-making. By analyzing huge amounts of data and deriving concrete business insights, we enable our clients to respond quickly and accurately to changes in the market. Using the latest technology and business domain knowledge, we not only provide optimal strategies for our clients, but also get deeply involved in the execution phase. These are things that many firms and startups may tout. What sets Baycurrent apart from other companies is that we can provide this on the scale of a leading company in Japan. From proof-of-concept to full-scale implementation. From quick wins to core measures. We pursue business impact more than anyone else.

Featured Cases

Promoting Formulation Data Management

We established and managed a data management system for pharmaceuticals aimed at providing information on their proper use. By engaging multiple stakeholders, we successfully organized and visualized the data, and completed the design, development, testing, and release of a new system within a short timeframe. This system now accurately manages vast amounts of information on medical institutions and healthcare professionals, enhancing both data transparency and output efficiency. Additionally, it has optimized pharmaceutical distribution and promoted the appropriate use of medications.

Supporting Store Opening Strategies with Data Analytics

To identify new store locations that would maximize sales for a major retail company, we used Python to analyze 500 types of data, including demographics. We clustered 900 areas into eight categories based on statistical information and regional characteristics and developed a sales forecasting model. For metropolitan and major urban areas, we calculated detailed sales and ROI, while for regional cities, we created a model to optimize profitability. Ultimately, we developed a store placement strategy aimed at maximizing revenue, contributing to the client's market share expansion and improved profitability.

Introducing Business Intelligence to Electricity Pricing

In the B2B segment of an electricity retail business, we developed a Tableau dashboard to visualize the cost per customer and the potential range for price increases. By using this dashboard, the company was able to prevent missing out on revenue opportunities. Additionally, we visualized profitability by customer segment to enhance management accuracy. Alongside building the dashboard, we also promoted training, transferring necessary skills from data processing and formatting to analysis. This enabled the company to continuously identify customers with low gross profit margins and implement measures to improve profitability.

Cases

Data Analysis Specialist Training Program

We implemented a program to develop data utilization skills for the insurance industry. We provided both classroom and practical training, equipping sales staff with the ability to use data to solve client problems.

Optimizing the Energy Supply and Demand Balance

Supported one of Japan's largest energy companies in optimizing the energy supply and demand balance. Provided assistance from both operational and IT perspectives, achieving improvements in overall business efficiency and accuracy.

Promoting Data Leverage as a Key DX Strategy

We made operations that had long relied on "intuition and experience" more efficient by backing them up with past data. We supported the creation of highly "feasible" use cases, their prioritization, and the construction of prototypes.

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