about the author
@Dennis
Data analysis expert
Career traverses consulting companies, state-owned enterprises, Internet companies, small and medium-sized entrepreneurial teams
Committed to data application and data culture construction
Introduction: Usually, the self-awareness of data analysts is the data quantifier of the business and the data miner of growth. We are used to using indicators to quantify the performance of the business, but how should we start with returning to ourselves? How should the performance of data analysts be evaluated?
Simply put, its core idea is to quantify the daily work and value of data analysts.
Excluding the general standards such as values and execution ability required by the company's performance appraisal, we mainly discuss the quantitative methods of the analysts one by one around the specific work of the analysts such as temporary access, data board and thematic analysis:
1 Quantitative methods of data analyst work
Temporary access is the first job for an analyst to enter the industry, and it will continue in the future career; whether it is a boss or a business side, the first understanding of a data analyst is to find an analyst for data, what is the revenue trend, What is the effect of the event, push customer group details, etc. How to quantify this part of the work? One is the workload, how many requirements have been undertaken, how many data have been taken, and how many man-hours have been spent. This is the number we often see when analysts make summaries. However, the quantification of this dimension only reflects the investment of analysts and cannot fully explain the value to the demand; because in general, temporary access is to obtain data quickly. For the demand side, fast and accurate data acquisition is the core Appeal. Therefore, a more appropriate quantitative indicator for temporary fetching is the average completion time, which can be calculated by using the average time from demand confirmation to completion. The reference measurement standards are as follows:
The data kanban is in addition to the temporary access to data, the demand side’s second understanding of the data analyst. The cousin can produce temporary data, or make fixed demand into daily, weekly, and monthly reports, push emails, or even Through the internal data platform or external visualization tools, a relatively beautiful data board is launched. At this stage, the timeliness for the completion of requirements is not the most important requirement of the demand side. Analysts have relatively time to sort out, summarize and plan requirements. The accuracy and timeliness of kanban data become more and more important. We can measure the accuracy of the kanban data by the number of errors reported by the kanban within a period of time, or use the number of consecutive error-free days to convey this information. The timeliness of kanban data mainly refers to the refresh frequency of data. There is a difference in the value of real-time data and offline data to the business; of course, because this part of the content is more related to data warehouses and data products, it cannot be used as an analyst's performance alone. Assessment. On the other hand, data kanban actually has more operation and maintenance costs than temporary access; in internal assessment, the number of kanbans maintained by the same analyst at the same time can be appropriately considered. The reference measurement standards are as follows:
Thematic analysis is that data analysts are most willing to put in energy and hope to be recognized, and it is also the most difficult part of the overall work. Behind the temporary data access and the data board are potential thematic analysis, but due to various reasons, the demand side has already made a summary statement on this basis.
How to transform the former requirements into analysis requirements will not be discussed here;
2 Data analysis value quantification method
We assume that after we have a data analysis topic, how to quantify the value of analysis. First and most importantly, the value of analysis should be highly tied to the value of business. All business actions are ultimately aimed at earning more profits, that is, discussing from the perspective of increasing revenue and reducing costs; in an ideal state, we To evaluate the value of thematic analysis is to quantify the benefits that the analysis results can bring. For example, through special analysis, discover a certain growth point, which ultimately brings revenue growth to the company; or discover settlement loopholes, which ultimately saves the company. Of course, the final output is not always the result of analysis. Analysis is the starting point. There will be more implementation work in the follow-up. Therefore, the output brought by the calculation analysis will have a proportional coefficient. This proportional coefficient is based on the analysis. The role is drawn up. The above is the ideal state and the direction of the analyst's efforts; in actual work, it is often not easy to have a lot of such intuitive analysis output. We need to introduce another assessment standard, a comprehensive scoring of thematic analysis.
The comprehensive scoring of thematic analysis is based on the value, timeliness, expression, satisfaction and other aspects of the thematic analysis after each thematic analysis. The simple method can be through questionnaires and then in-depth The Delphi method can be used. Based on the comprehensive scores of each special analysis, we can count the comprehensive scores in the period to evaluate the analysis results of the analysts in this stage. The reference measurement standards are as follows:
The above are the dimensions, indicators and measurement standards of the performance appraisal of data analysts. The weights of different dimensions can be adjusted according to the different situations of the analysts. The recommendation can be 334. For junior analysts, the assessment is mainly placed on temporary access and data board; for senior analysts, the weight of thematic analysis has higher requirements.
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