Founded in 1992, Jieshun is committed to the construction and operation of smart parking ecology relying on the software and hardware products of smart car dealers and pedestrian entrances and exits, and is the pioneer and leader of intelligent management of entrances and exits and the construction of smart ecological environment.
After nearly 30 years of development, it has become a leading enterprise in the field of smart parking in China. The company integrates research, production and sales, with two professional production bases, 10 R&D centers and more than 160 branches, serving major cities in China and more than 100 countries and regions around the world.
Customer Challenges
With the continuous development of the business and the high cost of upgrading the business system, the basic data extracted from the performance appraisal is inaccurate and the outgoing reporting tools are outdatedIn the face of the need for corporate executives to grasp the business status in real time, it is difficult to report quarterly and annual performance, and they have been half-manual and half-systematic, so they need professional big data platforms and BI analysis tools.
Lack of professional big data platforms and BI tools
The data report is processed by the system in a comprehensive way, such as simple processing by the system, system reprocessing, and human participationWith the help of SAP non-professional tools, there is no professional big data platform to implement data inconsistency, OneID, feedback business system and other work
The data quality is poor and the data standards are not uniform
The report data is inaccurate and there is no data standard;There is no guarantee of data quality, and there is no reserve of working methods;
Business needs can't be met
The chief financial officer cannot obtain accurate and timeliness business data, and it is difficult to evaluate the performance of the department and personnel, and the technical feedback is inefficient and cannot meet the business needs
Lack of data-based talent pool
There is a shortage of data technology and expert talentsCarry out data research, data analysis, data governance, and data asset inventory. The cost of recruiting data talents is high, and the company is currently in a stage of rapid business growth, and Jieshun has no clear development strategy for the data sector.
Solution
Big data platform construction
Introduce a professional big data platform to solve the current situation of lack of big data tools internallyIntroduce professional BI tools to solve the current situation of no professional reporting tools internallySolve the data silos of internal business systems, data quality, and the data status quo of oneid that cannot be solved by business systems
The standard construction of the indicator system is 0 to 1
The construction of the six major performance statements of the contract category and the index standard system of the profit and loss expense report from 0 to 1;Cultivate internal professional big data analysis talents to build Jieshun data business development methods, methods, and processes;From the 0-1 construction data work to other business areas, the party will be promoted to other business areas to achieve a point-to-point approach
Enterprises empower big data talent reserves
Cultivation of big data professionals, with added value to the project;Big data ETL engineer knowledge transfer, practical training;
Data quality, data governance, data inventory and other organizational empowerment, they have the ability to solve data problems, and middle and senior leaders understand the implementation partyFollow-up enterprises to achieve their own big data development, whether it is organizational level, human level, technology and business level capabilities.
[Project Results].
The construction of the index system, the establishment of the company's standards to the index system management and implementation mechanism;
Data governance, data quality, data security scheme design;
Realize the efficient and accurate performance appraisal data of enterprises;Support for business decision-making;
Big data talent growth and reserve;Experience has been accumulated in the follow-up development of big data business.
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