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Solution
Today, the Data analytics represent a critical area of evidence-based HR where people professionals need to possess an in-depth understanding of use of organisation data (CIPD, 2022a). This is since it represent a significant source of evidence in HR. Nevertheless, a common challenge impacting people professionals internationally is assumption that they are not numbers of people but people. In CIPD (2022a) factsheet, Data analytics is categorised as a new area of people profession. It entail using people data in-depth and organisation systems for informing best practice of developing improvements and interventions leading to improved people practice profession and business outcomes.
The identified challenge is an attribute of the following issues;
Low in skills and capability– In Personnel Today (2023) report, it hypothesis that in year 2023, a significant skills gap amongst people practice professional is Data analytics and data analysis. Considering Saudi Aramco case, this inform on the need for building on skills and investing in technologies to contribute to data-based decisions.
Lacking confidence– The people professionals similarly do not have sufficient confidence to pursue mid-level and sophisticated analysis of the people data. This is supported in Persaud (2021) noting that a partly 21% of people professionals note as having the confidence to adopt advanced techniques such as predictive analytics. For Saudi Aramco, this contribute to existence of unlocked skills amongst people practice professionals.
Lack of credibility– People practice professionals tend to lack sufficient credibility in terms of statistics and numerical skills and capabilities. For instance, in Saudi Aramco, only 36% of finance teams are in agreement that HR demonstrate numerical and statistical skills. This is with 37% believing people professionals demonstrating expertise for people data.
In an event these hindrances are eliminated, for an organisation such as Saudi Aramco, they would benefit from the following areas of using data analytics;
Aligning people data with organisation data for improved decision making– Considering Saudi Aramco organisation objectives, it entail to provide reliable, affordable and more-sustainable energy. Similarly, their people data would need to be aligned to this objective. For instance, the number of employees to be resourced, the amount of resources to be budgeted for people practices, career development opportunities would be targeted to the measurable objectives. These findings are supported by de Brito (2020) research using data in Post-COVID-19 pandemic and identified data analytics as enhancing alignment of different teams, using resources, planning and processes. The outcome of this in an organisation such as Saudi Aramco achieving sync of their critical organisation priorities. This is with appropriate resources allocation and promoting entire organisation objectives achieved with success.
Designing and Implementing HR Activities– In AIHR (2023a) report, it highlight that analysis of internal data, research-based practices and studies integrated with expertise judgement, experiences, values and concerns, people professionals would apply evidence-based decisions. This is contrary to reliance on the feeling of the employees in eliminating any form of biasness, temporary fixation and inconsistent practice. For instance, considering Saudi Aramco case, through the use of Data analytics and data, it would be possible to identify best practice of increasing recruiting efficiency with approximately 80% and achieve a decreased attrition rates with upto 50%.
Achieving Cost-Savings– As evidenced in Suri, and Lakhanpal (2022) report, Data analytics leads to possibility of entities optimising spans and layers which could lower costs and as such improving overall revenues. In Saudi Aramco for example, by adopting the Data analytics, it would be possible to identify the most appropriate employees team size which would contribute to delivery of an optimum commercial-based performance. Further, Suri and Lakhanpal (2022) note that Data analytics assist an entity in allocating resources in an efficient manner through noting likely value for resources allocated for various roles. For instance, taking a case of Saudi Aramco, in an event their data evidence that a specific L&D program (coaching or mentoring) harness staff performance and revenues, this would be appropriate for investment. This would be appropriate for cutting down immense costs which do not offer similar values. Similarly, using a recruitment strategy (job boards) can lead to consistent resourcing of highly qualified employees with sufficient skills to execute their functions. In this regard, a decision can be made of investing more resources in such a strategy and lower overall spend on other resourcing approaches which end up offering lowly qualified employees.
Staff Turnover Rates– According to Tursunbayeva et al. (2018), the employees turnover is an appropriate metric which is used to inform the number of employees leaving an entity within a specified period of time which can be every month, quarter-basis or annually. Hence, for Saudi Aramco, using the data analytics on employees turnover, it would be possible measuring number of employees leaving, rate of their leaving and overall financial implication on the organisation and turnover risks of their existing employees. The outcome of this would also entail identifying if the leaving employees are the high performers or lowly performing staff. From a basis point of view, low performers would be required to leave Saudi Aramco with high performers retained for long in the organisation. Similarly, application of the employees turnover data would assist to design best recruitment and retention approaches.
There are also drawbacks of using data analytics for informing business decisions in the case of Saudi Aramco, these include;
Low Quality Data– Considering Saudi Aramco case, a major drawback of use of the data analytics would include possession of appropriate data which is of good quality. Even with the organisation having the appropriate metrics and techniques for data collection, the quality would be directly impacted. According to Abkenar et al. (2021), there exist instances where data is non-available or missing for appropriate analytics to be pursued. With the data quality being poor, Saudi Aramco decision made would also be poor.
Privacy concerns– The process followed for data collection, analysis and interpretation could be impacted by privacy concerns. These concerns impact on online transactions and subscriptions in place for organisations services used. The data sourced could similarly be adopted contrary to individuals, countries and communities. Entities are as such required to manage data sensitivity, anonymity used and data sensitivity managed. For Saudi Aramco case, data can be breached in regard to trust lost hence negative implication on the organisation operations.
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