Sharing ideas for building resource prediction digital models

Business Background

Resource forecasting is a link in the project management process, that is, by building a suitable data model, we can effectively predict future project human resource investment, which can be completed more accurately. Project resource planning and the ability to promptly identify problems and make relevant adjustments.

Problems and pain points

There is no effective data to support resource usage during PM scheduling. Each time scheduling needs to be communicated with each R&D team TL, which will cause a lot of problems. communication costs.

Offline maintenance project resource investment information will generate a lot of workload and cause additional management costs for the R&D team and PM.

Manual maintenance will lead to inconsistent standards among teams, making it impossible to carry out large-scale promotion.

Solution

[Central idea] Through the daily project management process, the purpose of resource forecasting can be achieved without adding additional burden to the project management process.

3.1 Basic requirements

##3.2 Specific steps

• Activity 1: Conceive the effect - build data model - (direct/data processing) - establish data source

• In the previous chapter 3.1 The report mentioned is the desired effect.
• The parameters and basic functions are the data model and the data source. Obviously, these data sources cannot be directly applied to the effect display, so data processing is required.

• Activity 2: First create a demo through simple tools, confirm the feasibility, and gradually optimize according to the usage process
• I chose to perform Demo processing through Excel. For details, please see "PMO-Resource Forecasting_Template" at the end of the article.

• Activity 3: Utilize existing platforms and tools to go online

On the premise that the data results are stable and reliable, you can start planning the tool online. After all, Excel will be very slow when processing a large amount of data.

Business Results

• # Effective data can be provided to support query of available resources during PM scheduling.
• Reduce investment costs in R&D and test management. Through the daily project management process (project overall axis and project member investment), only two steps are needed to achieve the goal of resource forecasting. [Optimization points are gradually discovered during use, and a simpler prediction model is currently being designed to achieve non-sense prediction]
• Establish a more scientific and systematic data prediction model to strengthen Basic capabilities of digital management and provide analysis reference for deviations in resource investment.

Planning and thinking of digital management

• The basic data model of data source and processing should be fully considered when designing. This will facilitate secondary processing later.
• Try to choose online tools that meet your daily work habits. You can submit your requirements to the tool R&D team, or you can learn and develop them yourself. Because I am a PM, I have summarized a set of information suitable for non-R&D students.
• Discover pain points in daily work, summarize rules and methods, and then refine standards and processes through small-scale verification, and finally realize digital management actions.
• Behind every number are real projects and people. The key lies in how to apply these numbers.
• If they are copied and copied for the purpose of reporting, the participating students will doubt the meaning of these numbers; if they encounter problems, TL and PM should give feedback and increase what should be increased. Making things together for the sake of making things together, dialectical execution.
• If digital management is combined with monthly industry research meetings, demand ranking, demand scheduling, etc., and used to analyze positioning and assist decision-making, it will be very valuable and belong to daily life. management part.

"PMO-Resource Forecast_Template": ​https://zhuanlan.zhihu.com/p/547637165​

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