The Cruciality of Data Quality and How Organisations are Getting it Wrong

Theo Davey 2019

Theo, why should businesses care about the quality of their data, for example their employee experience data?

Theo: ‘Analysing data will improve your business, but only if that data is accurate and relevant. For instance, the only way you can attain accurate data is by asking the right questions. The questions asked in these surveys have to be relevant, engaging, and open-ended. This way employees are more likely to respond with accurate, genuine and useful answers.’

Where do most companies misjudge the data analysis/ data quality process?

Theo: ‘A lot of companies think that the quantity of data is the most important factor. Some organisations will conduct annual, quarterly or even monthly surveys. Thereby building up a considerable body of data. But when, or how often you conduct surveys is not the critical issue. What companies cannot afford to get wrong is ensuring the data they collect is rich. The more personal experience and knowledge included in the data the richer it is.  If the data is not rich, it does not matter how much you collect.  This data will hold little value.  

We handle pilots from many international companies. A common issue we find when analysing their datasets, for example, is that employee emotions can be falsely influenced. This is due to the way questions are worded. Questions must be open-ended so that responses are not swayed or limited.

For instance, if asked an overly positive question (‘Why do you love this company?’), you are only going to receive positivity. A better question to ask would be ‘What are some of your most notable experiences working at this company?’.

It’s also about engaging with your employees. They need to believe that the information they provide will have a positive impact.’

Data quality is not just important for employee feedback though is it? Do you have to ask different types of questions to customers to gain insights into a product/service when conducting consumer research?

Theo: ‘With employee experience surveys the goal is to improve the employer brand. This is both internal and external. With customer experience, we can be talking about…

  1. Improving the overall brand
  2. Improving a single product
  3. Entering a product into a new market

So, the actual questions will be very different, but the question design is the same.

Similar to employee experience, customer/product/service surveys should be open-ended. You should always be provided with enough space to write what you want, rather than limited to one of a selection of predefined answers. This is a reason why e-Commerce reviews are so valuable to a Customer Experience analysis. The review is an individuals’ unrestricted and unstructured knowledge and experience of a product or service.’

Pansensic Analysis

Quality data is only possible with complete transparency. To what extent do you agree with this statement?

Theo: ‘How transparent data needs to be, depends on how granular the company wants to go in its analysis. Obviously, you need to be careful about what data is visible and to whom. Especially with new GDPR protocols in place. Companies have to be careful. But it’s not actually complicated to be compliant.

But, obviously the point of these surveys is it get improvement insights. If employee names are required, responses may not be as open or honest. This is because, depending on the organisation, employees may be fearful of the consequences of speaking their minds. Therefore, anonymity is often the most common practice. But in our experience, it doesn’t limit the value of the insights extracted.

How do you overcome issues with fragmented data ownership?

Theo: ‘We work with global companies who employ thousands of employees and have consumer bases in the millions. Naturally, there are going to be different strategies and aims throughout the different business units who have different objectives. But if all these units align their overall business strategy, it will not matter if the data is fragmented.’

If businesses follow all this advice, what benefits can they expect?

Theo: ‘First, and foremost, businesses will increase employee and consumer engagement. If employees believe that their opinions are being listened to and acted upon, then you get engaged employees. Engaged employees are happier and more motivated in their work. A happy workforce is a huge bonus, in every respect.

With employees being engaged emotionally, they are more relaxed about sharing their thoughts on…

– Job roles

– Likes

– Dislikes

– What they want to improve

So, as a business you will receive high quality data to support growth and benefits including…

  • Engagement
  • Attraction
  • Retention
  • Loyalty
  • Reduced Stress
Employee engagement

Say you now have open-ended questions, what kind of comments do you hope for?

Theo: ‘What we want are rich comments. These are comments in which employees or consumers express themselves openly and at length. These types of comments provide us with the best insights.

Using employee experience as an example, from these comments we can provide companies with three different types of insights.

  • Top tier insights are what the board will want to see. These are the key areas of improvement from a top-level perspective. These include identifying which parts of the organisation are under or over performing. For instance, Training and Personal Development may be well received and applauded by the workforce. Whilst, Roles & Responsibilities or Software & ICT may cause a lot of negative emotion.
  • Middle tier insights include the analysis of different departments associated with a single organisation. This analysis reveals overriding themes, as well as the differences of employee experience between differing locations. Providing middle tier actionable insights is extremely helpful for senior management because they can start to make informed improvement plans. We do this by drilling down into where an organisation needs improvement. We can then benchmark regions/countries/divisions and even business units. Pansensic do this to establish where/who are outperforming/underperforming.
  • The bottom tier highlights the granular evidence and contributing factors that make up the insights. Drilling down to the lower-levels of the organisation (departments & business units) gives us a granular approach to providing improvement-driving insights. These insights can, firstly, improve the employee experience within the lower levels of an organisation and, secondly, align the bottom tier insights with the middle and top tier insights. In doing so, organisations can establish key improvement strategies organisation-wide.’

 

The data analytics field is vast. What drew you to data quality in particular?

Theo: ‘My BA was in business management, with a specialisation in marketing. In my fourth year I decided to go into Compliance. I was an AML Compliance Associate for around seven months based in Vilnius, Lithuania, and really enjoyed it. But, after finishing my degree, I wanted to come back to England. I saw the most exciting future for me back in the UK, a country at the forefront of next-level data analysis.

I met Pansensic’s CEO, Paul Howarth. Paul demonstrated to me the Pansensic aim, what they did and how they have helped organisations. He showed me the Pansensic Hybrid Text Analytics (HTA) engine, and how it could determine which emotions were being shown in comments. I had never seen anything like it. I found it absolutely fascinating and was immediately hooked.

Rich data is highly important to establish key insightful emotional and improvement drivers. With powerful experiences, Pansensic can explain why employees/customers are dissatisfied and, more importantly, where improvement is needed.’

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