Data to aid workforce retention. Issue 2, Care England - Savings, Solutions, and Sustainability

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Data to aid workforce retention

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In this article, Jim Thomas, a Social Care and Health Workforce Expert, explores what data can help, what data to ignore, how to spot a trend and how non-numeric data can help to retain the workforce.

The article will focus on:

• The impact of pay on retention.

• How to understand sickness trends.

• In-work benefits.

• Flexible working.

• How to project future retention.

Which data to focus on

Three rules to consider:

1. Have I got ready access to the data?

2. Is the data in a format I can use?

3. Does the data help make decisions I can explain to others?

Data to focus on might change depending on what you are trying to understand, how easy it is to access in a format that makes sense and what you want to use the data for.

For workforce retention, important data includes exit interviews and supervision records. A well-designed exit interview gives an honest picture of why someone is leaving be that pay, promotion, flexibility, benefits, their manager, or co-workers. Supervision records can offer a picture of how staff feel. If there are no supervision records, you might wonder if the workforce has a safe space to explore their concerns. If you look at workplace incidents (falls, moving and handling mistakes and medication errors) you might find places where the workforce does not have regular supervision, and this might link to issues retaining workers in a particular part of your organisation.

Which data to ignore

Choosing which data to ignore is equally important as you can lose a lot of time looking at data that doesn’t aid decision making. Ask yourself three questions before looking for data:

1. Can I understand and explain the data to others without needing specialist help?

2. Will the data help compare my workforce with other similar workforces meaningfully?

3. Is the data recent, or over a long enough period to be useful? Continued →

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These questions will help decide which data to use and what to ignore. If you need external help to understand the data, are any costs associated? Also, will external data analysis be able to understand the context in which your workforce is operating fully?

When comparing data, you need to decide how similar your workforce is to the comparison data. Is it helpful to compare retention data for home care workers and residential care workers? Probably not, as the factors that people have in mind when they choose to work in a certain type of employment will differ.

Some people may prefer working alone or one-on-one or in the same place every day in a residential care environment. Some people might prefer work that fits in with other personal commitments, or roles that don’t require them to work in the evenings or at weekends. Some roles are cross-transferable and could be useful to compare, such as registered managers. You might want to look at the factors that keep people in those roles (such as pay, support, training opportunities and personal development opportunities).

How to spot a trend

A trend is an up or downshift in data over time. To spot a trend make sure that the data is specific enough, over a long enough period, and can draw meaningful conclusions. You also need to think about anomalies that might impact the validity of the data. For example, the pandemic. However, it’s still worth asking – what did we do during this period that improved or didn’t improve retention? You might have a particular part of your workforce where turnover is much higher than other parts of your workforce. You could look back over the last five years to see if this is something that has just occurred or has been happening for a longer period. The questions you might then ask are: Has something happened in that workplace to create this trend? Is it that workers are being asked to do things that they don’t feel are part of their role? Has there been a change in management that has had a positive or negative impact on the workforce? Have contracting arrangements changed, impacting job security? If the trend shows that turnover always goes up in school holidays, think about how you can adapt your workforce patterns of employment to reduce turnover.

How to use non-numeric data

Non-numeric data includes case examples, personal testimony and witness statements. This data can help explain decision making and add detail to the numerical data. Data might show a reduction in turnover and improved worker retention over the last six months, but it won’t tell you why. For example, if you add a narrative to the data that explains how a new training programme has made the workforce feel more confident and valued, you add colour to the data that gives a more rounded picture of what does and doesn’t help to hold on to the workforce.

The impact of pay on retention

Pay is one of the factors that influences retention, but it can be a red herring. People will change jobs for improved pay and most people who work in social care are not paid at a rate comparable to the knowledge and skills that are required to work in social care. It can be a red herring because often the wrong data is used to make comparisons about pay. To change the narrative, you need to change the data comparisons you are making to challenge pay rates and stop comparing roles that are paid at a similar rate to social care roles (for example, retail workers and leisure industry workers) and start comparing roles based on like-for-like knowledge and skills.

Like-for-like roles include health care assistant roles, nursing roles, allied health care roles, and technical roles in industries such as engineering and specialised sporting support roles.

The other thing to consider when looking at pay data is other linked benefits, such as enhanced pension provisions, free uniforms, family support, annual leave provision and overtime rates.

How to understand sickness trends

To understand sickness trends, you need to look backwards and understand if there are trends. For example, times of the year when sickness is higher (school holidays, certain national holidays). Is there a link between short-term sickness and longerterm sickness? Are there different levels of sickness amongst people in different roles? If you combine your exploration of the data with back-to-work interviews you will begin to build a picture of the factors that impact sickness and what you might do about it.

For example, a gradual or sudden change in the level of support that workers have to offer people could result in more injuries at work; for example, moving and handling injuries and personal harm from supporting people whose behaviour is challenging. You might need to implement new training and development programmes and review the impact these programmes have on sickness levels.

In-work benefits

In-work benefits are closely linked to pay such as enhanced pension provisions, free uniforms, family support, employee assistance programmes, annual leave provisions, and overtime rates etc. From a data perspective, you need to test the impact that different in-work benefits might have on retention. The starting point for this should be the cost of providing an in-work benefit. For example, improved overtime pay may reduce the use of agency staff, which may retain the workforce more effectively and result in staff and the people they support feeling better about the place they work as well.

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→ Continued →

Flexible working

Flexible working can also be linked to pay and in-work benefits and comes in many forms. It can be a contract where someone only works on specific days, doesn’t work during school holidays, or takes account of someone’s additional family care responsibilities. This might mean that sometimes they need to change their working pattern at short notice. For example, if someone can only work 10 hours a week during term time and you can accommodate that, you might increase workforce retention. This is because you can show how, as an organisation, you can flex the way you are organised to meet not only the needs of the people your organisation supports but your workforce as well.

How to project future retention

This is one of the most difficult things to do and you need to look backwards and explore the factors that have enabled you and other organisations to improve retention. You could start by using something such as the Best Companies survey to help you understand your workforce. For example, through such a survey you might discover that your workforce feels that support that improves their wellbeing at work or home is not as good as you thought it was. You can then look at what you can put in place to improve wellbeing and then do the survey again after 12 months to see what has changed.

Where to find the data you are looking for

Any source of data is only as good as the accuracy with which it has been collected. How well it has been kept up to date, how long it has been collected, and how many people/organisations have contributed to it. A survey of 10 is less useful than a survey of a thousand when it comes to drawing conclusions from the data.

Skills for Care’s Adult Social Care Workforce Data set is an important source of workforce data. It is regularly updated and can be explored at an individual service level by a group of services in a local area, and by a care group at a regional and national level. Because there is so much data in the Adult Social Care Workforce Data set it’s important to know what you want from it before you dive in. If you are looking at it from a retention perspective, then look for these three things:

1. Pay rates.

2. How long do people stay in particular jobs?

3. The age ranges of people in different roles.

These three data points will help build a picture of how to compare other similar organisations.

The Office of National Statistics is also a valuable source of data (although less specific to the social care workforce) but can help compare your workforce data with other workforce data sources. If you are looking at data from a retention perspective, then look for these three things:

1. Pay rates for similar jobs.

2. Workforce mobility – how long do people stay in different jobs?

3. The age range of workers in different industries.

Be open to case examples, personal narratives and witness statements to add context.

These three data points help us to understand what other industries are doing to retain their workers and potential learnings for your organisation.

The Commission for Care Quality’s reports such as The State of Care are a useful source of generic data to help decide on the retention issues you might want to explore. Individual inspection reports are a way to explore retention challenges for similar organisations. Identify four similar organisations (homecare/ residential), location (rural/city/town) and number of employees. Choose two reports that are rated outstanding and two that are rated inadequate. Then look at the following:

• Turnover of workers – what percentage leave per annum?

• Manager stability – how long do managers stay in post?

• Absence rates – number of absences and duration.

This data might not always be easy to find but will give you an indication of things that you might be able to use in your organisation to improve retention.

Less is sometimes more

Data is one of the many tools to help with workforce retention and the amount available can be overwhelming. Therefore, it’s important to think about what data to use, why you want to explore it, and how it can help. I would urge you not to limit yourself to just numerical data and to be open to case examples, personal narratives and witness statements to add context. Sometimes, less data can often be more than enough.

Jim Thomas is a Social Care and Health Workforce Expert. Email: jim.thomas@longhouseman.co.uk

@Longhouseman

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