Abstract
The study shows our findings regarding the initialization and implementation of data science projects in existed business processes. The index readiness for intelligence or IR4I is proposed as an indicator of understanding about the readiness of your business processes for data science solutions. The index is based on the min-min convolution of various indicators: (i) business processes maturity indicators, (ii) indicators of the level of automatization and digitalisation of business processes, (iii) extract - transform - load (ETL) processes maturity indicators, (iv) data science infrastructure and technological stacks maturity. A new method of the IR4I index calculation is provided and its contains of six steps. Use case is based on real world task related to daily electric energy consumption forecasting for daily demand ordering. This example shows the application of proposed method and possibilities for improvement of business processes towards its intelligence and efficiency.
M. Shcherbakov — The reported study was partially supported by RFBR research projects 16-37-60066 mol_a_dk, and project MD-6964.2016.9.
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Notes
- 1.
The superscripts shows the number of a group and subscripts is a number of an indicator in the group, e.g. \(\alpha ^{(i)} _{j}\) is j-th indicator in the i-th group.
- 2.
Also, there is no specific protocol for KPI evaluation.
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Acknowledgments
The reported study was partially supported by RFBR research projects 16-37-60066 mol a dk, and project MD-6964.2016.9. Also authors would like to thank Pavel Vorobkalov for fruitful discussion and anonymous reviewers for fruitful remarks.
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Shcherbakov, M., Groumpos, P.P., Kravets, A. (2017). A Method and IR4I Index Indicating the Readiness of Business Processes for Data Science Solutions. In: Kravets, A., Shcherbakov, M., Kultsova, M., Groumpos, P. (eds) Creativity in Intelligent Technologies and Data Science. CIT&DS 2017. Communications in Computer and Information Science, vol 754. Springer, Cham. https://doi.org/10.1007/978-3-319-65551-2_2
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