ABeam Visual Analytics

Data Utilization Service that Corresponds with
Constant Changes in Data and Business Requirements

Many companies do not fully utilize their developed management dashboards/cockpits on a continuous basis. Reports are often made with repeated usage of the same layouts and dimensions, causing top management and even the corporate planning analysts to lose interest in the outcomes.
In recent years, the advancement of data visualization technology has allowed for outliers and trends to be easily detected from mass data as well as a wide variety of combined data to be analyzed. ABeam Consulting will support companies with data analytics acceleration based on its rich experience in BI implementation, industry knowledge, and project management capabilities.

Data Utilization Method

The key to achieving optimal actions through the utilization of data, is to share the various findings from its analysis. Checking of data on a periodic basis with a fixed point of view will not produce effective measures, especially without making comparisons or obtaining information on the contributing factors.

Analytics Flow


Analytics Cycle

This approach involves the establishment of an analytics flow based on the clarification of “what data to be checked,” “how the data will be displayed,” and “who the data will be checked by”. The establishment process consequently requires a large amount of time and cost. The approach additionally has little flexibility in meeting additional requirements frequently raised and lacks capability of offering solutions for the requirements within a short period of time.


This approach involves the development of an analytics cycle, in which data analysis is conducted in order to find changes in business conditions as well as their contributing factors. Valuable findings are made through deep data analysis, considerations on the contribution factors, and comparisons with additional criteria. Findings are then shared with the decision makers for concrete actions to be executed. This approach allows for the cycle of sharing findings and executing actions to be repeated with speed.


A data analytics design that only involves data filtering will also result in little flexibility for additional requirements as well as limited utilization of data, the available scope of data restrained within the requirements initially defined. In many cases, time and efforts will exceed what was initially expected in order to include the followings: additional dimensions, layout changes, and further detailed data segments for deeper analysis.


Flexibility is the key in data analytic design: speedy availability of ad hoc analysis based on the users’ needs is critical, with changes in reporting data or analysis criteria. The Analytics cycle approach allows for the following steps to be performed repeatedly within a short period of time:import data > visualize data > make findings > make improvement. This repetition will contribute to critical findings by the stakeholders, active discussions, and consideration/execution of actions for the findings.


Project Approach

ABeam’s project approach for visual analytics consists of five steps that will be repeated in promoting deeper analysis within a wider scope.First, the current data will be analyzed through filtering and comparisons. Next, interviews will be conducted with the stakeholders based on the analysis results of the current data in order to share potential issues and requirements. New data scope will then be determined in accordance with the requirements, and further analysis and visualization of data will be conducted. Lastly, workshops will be held with Persons in Charge of Operations as well as IT in order to confirm new analysis results and incorporate additional requirements. The project will also conduct the following tasks in order to determine Next Actions and subsequent themes of analysis, promoting the continuous utilization of data: examination of upstream systems and business processes, and considerations of necessary measures.

Case studies: Analytics Cycle Approach

Past data utilization projects in which companies have implemented the “Analytics cycle” approach have had successful outcomes: Data age with a limited scope, allowing the project to continuously consider/execute concrete measures on various issues in accordance with scope expansion.

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