Text | Sailor Brother, FanRuan Data Application Research Institute
This article comes from: Knowing the column " FanRuan Data Application Research Institute " - data dry goods & information center
Whether at home or abroad, the road to building BI and analysis platforms for most companies is not smooth: First, they have insufficient understanding of their own environment and needs, and they fail to beat the snake and hit seven inches, resulting in low performance and output; second, they only focus on At present, the failure to consider future variables has resulted in the inability of BI construction to extend in an orderly manner to respond to needs; third, insufficient experience and level make it difficult to control the BI construction roadmap, resulting in many detours and even backtracking.
In this regard, Gartner has launched a BI maturity model to help enterprises use "ITScore for BI and Analytics" to conduct maturity assessment, clarify their current characteristics, the stage they are in, and what steps to take to enter the next stage, so that enterprises' BI and The construction of a data analysis platform has a path to follow and a law to follow.
The Gartner BI Maturity Model is divided into five stages, which are:
1. Unaware
In the unknown stage, the enterprise does not have BI informatization, all analysis is based on excel, the analysis is also temporary, and there is no complete analysis strategy and system. The problems at this stage are also very obvious. The report needs to be repeatedly produced and processed many times. The labor cost is high and the timeliness is poor. The report may be useless, or the data may be wrong but cannot be verified. Various problems make data-based decision-making known. Empty talk.
2. Opportunistic
In the speculative phase, business units pursue their own BI and analytics initiatives, taking responsibility for data analysis themselves. There are multiple business systems in the enterprise, such as CRM, ERP, BPM, etc., and some reports and analysis pages are built into the business system. The correlation of each system is not strong, and the problem of data chimneys and data islands has always existed. It is difficult for business departments to do overall and global analysis, and the data and indicators of various departments even conflict. For reporting and analysis, business departments may use some data integration, intermediate databases and analysis tools alone, which eventually leads to the existence of multiple source databases, BI platforms, dashboards, etc., which are scattered and stored in different places. Although this model can meet part of the needs of business departments, knowledge cannot be shared, excellent projects are difficult to expand to solve other uses, and enterprises are still in a state of low economies of scale.
3. Standardization stage (Standards)
In the standardization stage, people, processes and technologies are coordinated in the enterprise, data can support users to make analytical decisions, and organizations begin to turn to shared services to determine technical standards. At this stage, the enterprise also has a BI Competence Center (BICC) composed of business departments, IT departments and data analysts to share knowledge and improve the consistency of business systems or information use. Business departments and IT departments jointly build relevant business analysis and sharing systems, and at least one senior executive becomes an expert in business data analysis. Technical standards began to emerge, including information infrastructure, data warehousing, and BI. For the first time, enterprises have reduced the overall cost of BI and analysis work by improving coordination processes and technology standardization. However, the adaptability of BI and analysis systems at this stage is still very low, enterprises have not yet experienced economies of scale, and managers have insight into other processes. Still not enough.
4. Enterprise stage (Enterprise)
At the enterprise level, the enterprise is performance-oriented, and the enterprise operation and analysis indicator system has been perfected, with consistency and stability . In the role of substitution, senior management should give more human and financial support to BI construction. At this stage, the middle and low levels of the company can use BI and analysis systems for reporting and analysis. Although BI and analytical systems have become more efficient, the use of growth and costs are still high, and companies must ensure that there are high-level talents in different fields to properly support the application of new technologies and new models in each business unit.
5. Transformative
In the transformational stage, BI and analysis systems have become a strategic initiative for the joint operation of enterprises and IT departments, and are supported and managed at the highest level of the enterprise. Enterprises regard informatization as a strategic asset, and use BI and analysis to create benefits and improve operations. Efficiency to provide customers with first-class service. The enterprise performance metrics framework extends to relevant partners and customers, and all stakeholders use BI and analytics systems to respond to changing business analytics needs and make transformative decisions. At this stage, BI and analytics systems are extremely flexible, allowing users to perform a variety of self-service, predictive, and prescriptive analytics.
In summary, the characteristics of the different stages are as follows:
Development at different stages: