Filters enable you to gain a more granular view of your workforce data. They are consistent throughout the platform.
Introduction to filters
Filters provide a way to refine the data by workforce-related criteria, such as location, organisational unit and employment type. Filters are consistent on every report page.
- Once criteria have been selected and unselected from the filters, the filters are persistent across every report until reset.
- The filters can be modified any time.
- The set filters will also apply to any data extracts you download.
- Changed filters will be highlighted so that you can keep track of what's changed and what hasn't.
- To reset all the filters, select the Reset button at the right-hand side of the filters.
- If you're planning to use a specific set of filter criteria often, you might want to save it so that it's not lost when you next refresh your filters.
- To save, select the Save icon at the right-hand side of the filters.
- When you select the Save icon, you'll be asked to name your filter.
TIP: It's not possible to edit filter names once you've saved them, so we recommend you plan a naming convention. Over time, as your list of saved filters grows, a clear naming convention will help you easily identify your filters.
- To find a saved filter, select the Save icon to view a list of all saved filters and click on the filter name to use it.
- Saved filters can also be deleted from this list.
MODEL SCENARIOS BY YEAR AND TECHNOLOGY
There are two filters within the Scenario tab, Technology and Years, to assist you to model different scenarios.
- Select specific technology types by one of 16 technology technology types. View the Technology Taxonomy for more information.
- Select the time horizon from between one to 15 years into the future. for more detail about the Years filter, view the FAQ's below.
These organisational units are unique to your organisation and have been supplied in your workforce data. This filter is useful for evaluating workforce insights within a specific organisational unit.
These locations are unique to your organisation and have been supplied in your workforce data. This filter is useful for evaluating workforce insights at a specific location.
These levels are unique to your organisation and have been supplied in your workforce data. This filter is useful for evaluating workforce insights at different role hierarchies in your organisation.
There are two filters, Job Categories and Job Streams, within the Jobs tab.
Job Categories: This filter provides an alternative, profession-centric way to refine your workforce data. These filters can be used instead of, or to complement, organisational units and other filters. Every job in Faethm’s Occupation Ontology is grouped into 24 major jobs categories (akin to high level job families) such as Engineering, Medical and Business Ops.
Job Streams: Every job in the Faethm Occupation Ontology is assigned to one of three streams that we use to model job seniority:
1) Individual Contributor
DEMOGRAPHICThere are two filters, Gender and Age, within the Demographic tab that can be used to filter to a specific gender and / or age bracket for a clear view of impacts on FTEs in those demographics.
About the Years filter
Where do I find the Years filter?
The Years filter is found in the Scenario tab, along with the Technology filter.
It defaults to being set at five years in the future.
Is the time horizon cumulative?
Yes, each subsequent year selected in the filter shows a cumulative total of technology impacts.
What is the purpose of the Years filter?
The Years filter enables you to view technology impacts on an FTE’s tasks (and hence jobs and related salary costs) at a specific year in the future. The time horizon ranges from one to fifteen years, allowing for the technology impacts to be compared over time.
Does the Years filter take into consideration technology your organisation has already adopted?
No, it does not. The technologies used in our model, which is described in greater detail below, are the emerging technologies that comprise our Technology Taxonomy.
Does the Years filter predict the future?
No, Faethm does not predict the future. Instead, the Years filter presents potential future scenarios. The scenarios are based on the exponential growth trends of emerging technologies - that is, the rapid growth and adoption trends of all technologies in our Technology Taxonomy. When evaluating future technology impacts on your workforce, this context should be considered and the insights on the platform should be evaluated in conjunction with other external and internal forces, which aren't included in our modelling, that may impact your workforce.
How does Faethm model the technology growth and adoption trends that inform the Years filter?
The AI we use, incorporating a Support Vector Machine and Neural Network, determines:
1. whether a task will be automated or augmented
2. by which specific technology in our technology taxonomy
3. when this will happen, based on the adoption curves
Faethm has developed adoption curves that are derived from proprietary modelling.
We model a set of around 150 indicators of technology adoption rates to rank country and industry adoption rates. The ranking is used to reduce the impact of each technology-task adoption curve based on the country and industry that a job is operating in. Our modelling includes a PESTLE analysis per country, per industry, to consider external barriers to implementation as well as other assessments and measures of adoption including historic analysis, survey data, and proxies, to solve for:
a) when the tech will be available
b) the extent of total adoption
c) the speed of adoption
Our machine learning algorithms are highly accurate with both precision and recall scoring in the range of 90 to 99%. This statistic tells us that our modelling is a robust approach to projecting the future impacts of technology.
What factors are excluded in the technology growth and adoption trend modelling?
Our Technology Adoption Model excludes disruptive influences (such as wars, pestilence or recessions).
Business Resilience: The filters
Faethm’s job recession resilience filters provide a view of which jobs have been resilient versus at risk, based on historic recession data, primarily the 2008 Global Financial Crisis. This filter is available only for those who have this additional platform module included in their Faethm license.
The pandemic essential job filter
This filter provides a view of which jobs can be essential to supporting front-line mitigation of the pandemic and the general operation of public services and a society. This filter can serve as a way to identify pandemic essential jobs and assess their human interactivity and remotability to ensure they can be productive or enabled with further support.
The categorisation of jobs categorised by Essential and Non-essential is informed by OECD standards (predominantly UK Government-led) and include health and social care, public safety and national security, food and necessary goods and more.
The job recession risk filter
This filter provides an indication of job types within your organisation that may be at risk during a recession, and the availability of certain types of jobs in the marketplace. The intent of this is to enable proactive measures to support workers’ job continuity, job transitions or outplacement, and to make more informed ‘build versus buy’ decisions from a recruiting perspective.
The continuity essential job filter
This filter provides a view of which jobs can be central or critical to supporting an organisation’s business continuity through times of disruption. There is limited business continuity research to inform conventions for continuity essential jobs and this can vary by organisation context. These categories can serve as a guide for your organisation’s analysis, and can be refined and updated based on your unique organisational context.
To support a guiding framework, Faethm defines continuity-essential jobs as:
Future-essential: deliver value to the organisations through a mixture of higher-level skills and knowledge that enable the future strategic direction of the business.
Operational-essential: keep the business running, a loss of an individual could disrupt business operations, lead to revenue loss, or impact the reputation of the firm.
Non-essential: jobs that are in high supply. For example, a store manager may be critical to the operations of a store; however, there is a larger supply of store managers in the market meaning it is easier to hire for now and in future.
This filter can serve as a way to identify core jobs and associated workers to prioritise productivity enablement for driving on-going continuity.
Future-essential: To inform future-essential jobs, Faethm applies a scientific approach that considers both value-generating skills and those jobs that are unique and hard to replace. Value-generating skills are skills important in the future of work, such as achievement-focus, social perceptiveness, problem-solving and empathy. Job specialisation/uniqueness is measured from those jobs in high demand but in low supply (suggesting these jobs have unique and in-demand skills). Faethm supply and demand assessment also considers the future automation. Together, these metrics identify a Faethm view of future-essential jobs in the organisation.
Operational-essential: To inform operational-essential jobs, Faethm has identified an industry-general view of jobs that can be core to organisation operations. These jobs are seen as essential to maintain through disruption as if there is a loss of an individual within these core areas, there could be disruption to continuity through a break or quality loss in process. Faethm’s view of operation-essential jobs can be used to help identify the key individuals in an organisation that should be deemed as central during times of business stress.
Non-essential: To determine non-essential jobs, Faethm applies a scientific approach that considers both value-generating skills and those jobs that are unique and hard to replace to determine those jobs that are either operational-essential or future-essential, the remaining jobs are considered non-essential.
Custom filters can be used to obtain more granular insights with data fields relevant to your organisation. These filters are defined by you at the outset, before your workforce data has been delivered to Faethm and ingested into the platform. Examples of custom filters that many organisations use include ethnicity, disability, and industry award rates.
Custom filters can be included at any time, so if you're finding that you need more customised filters, contact your Client Insights Manager. Providing your own organisational classification of continuity-essential jobs, level types (and other guide filters) is particularly beneficial as it will enable a more contextual categorisation of your organisation’s jobs and workforce.