Using issue-driven data to move toward
※Below is an excerpt from "Perspective II", "ABeam" Public Relations Report 2018-19.
Today, a major wave of creative disruption is overwhelming various industries. The question is: how can individual companies connect and share the data they possess to generate new value and services? Companies are hurrying to become Connected Enterprises, which forge links that transcend organizational, corporate, and industry lines; when they do so, however, it is essential that they reform their understanding of data in a root and branch manner. Akira Akaishi, who has worked with a large number of companies, discusses the heart of the matter.
Executive Officer, Principal
Head of P&T Digital Business Unit
Cross-industry data links are advancing overseas—Japanese companies must act now before it is too late
“Data-connected”—which refers to linking data between companies and industries—is progressing, with the aim of realizing digital transformation. However, data-connected is not being implemented quickly in Japan by any means.
Even when it comes to autonomous driving, Waymo, the self-driving technology company created from Google’s autonomous driving project, is said to clock 25,000 miles of autonomous driving per day—yet this technology is still very much in its infancy in Japan.
In autonomous driving demonstration tests, the actual distance drove correlates directly with improvements in software accuracy and, since the accumulated data has enormous potential to generate new businesses, it is preferable to commence development and testing as early as possible.
Of course, there are also examples in Japan of data-connected successes. One such initiative is supported by ABeam Consulting: four manufacturers from completely different industries have linked their data and, using consumer behavior information, have been able to provide new services.
Identifying what data is truly essential through issue-driven approaches
With the development of digital transformation, we are approaching an important turning point in how we think about data. When companies attempt to generate new businesses by sharing data with each other, their primary focus ought not to be on the data itself, but on issues and needs, and how to resolve or cater to them.
When phrases such as “Big Data” were in vogue, the majority of companies were of the mindset that“since such a variety of data is being accumulated, isn't there something we can do with it?” However, unless companies first decide their goals, and only then ask themselves “what data do we need to accomplish this?” they risk being overwhelmed by the data.
As people became more familiar with data and implemented processes of trial and error, they realized that they first had to define their usage goals and establish optimal usage frameworks; otherwise the data was of no benefit. Now, companies are trying to effect the major shift from data-driven approaches to issue-driven approaches.
Let us say, for example, that a company has daily sales report data stretching back several years; it would be difficult to arrive at new realizations from this data alone. Perhaps the daily reports are written in different formats depending on when or where they were created—this would make it impossible to analyze them in their current form. If a company wishes to gather and use data, then it must establish goal-driven frameworks before it starts data collection. If, for example, a company decides that it wants to monitor product sales trends throughout the year, and understand the relationship between best sellers, the weather, events, and customer attributes, then it naturally becomes clear what types of data they should collect.
Using data jackets to establish data markets
Going forward, as issue-driven data leads more and more to the creation of new business, there will be growing demand for platforms that enable large amounts of data from a variety of different fields to be freely seen and used. If we can establish environments that enable data—including existing open data —owned by various companies and organizations to be used according to different attributes and goals, then data use will rapidly increase.
At present, ABeam Consulting is focused on and deepening its understanding of the “data jacket” approach pioneered by Yukio Ohsawa at the Ohsawa Laboratory, Department of Systems Innovation, School of Engineering, The University of Tokyo.
Data jackets are structures through which data content is itemized in predetermined locations, for example on the cloud, so that it can be viewed by anyone—in much the same way as song data is itemized on record and CD jackets. It is similar to the book search system used in closed-stack libraries.
Data jackets do not only contain data names and content descriptions; rather, they also feature comments from the data owners, such as “this data can be used for this type of analysis,” which provide viewers with hints on how the data can be used. If data jackets are all organized in the same manner, companies can identify and access the data that will help them resolve the problems they face.
Such activities should enable companies to advance innovation depending on the data they use; in addition, using Connected Enterprises, they should be able to establish new businesses that provide entirely new value.
If cross-company and cross-industry data sharing become more widespread, there is even the possibility that a market will be created—similar to a stock exchange—in which high-value data is traded at high prices. The establishment of such a market would result in greater fluidity for data that has been stored but is currently unusable, and lead to higher-quality digital transformation.
Infrastructure is a shortcut to full use of data
Of course, it will take time for such an ideal can become reality. What, then, should a typical company do in order to establish a process of gathering, storing, analyzing, and using data? One way is for the company to start from scratch and develop its own tools; yet it is no simple task to continue to align these tools to a rapidly changing environment. Instead, the use of external, on-demand systems that feature pre-optimized data usage processes allows for data to be used in a more flexible and speedy manner; such external systems also enable costs to be reduced.
ABeam Cloud™ is one such system. Through system establishment, improvement, and integration projects in a wide range of fields, including ERP, ABeam Consulting has accumulated a wide range of knowledge and know-how when it comes to data. Using this experience to the full, we intend to provide support both for a data-connected society and for the new businesses that are generated therefrom.