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Can data analytics drive employee engagement and company culture?

group of young multiethnic diverse people gesture hand high five, laughing and smiling together in brainstorm meeting at office, company culture

Big data. For many of us, it’s one of those buzzwords that is overused, but not understood.

And yet, workplace analytics represents a crucial part of the puzzle for any company that’s committed to fostering a collaborative culture and creating a team that’s driven to deliver the best service for its customers.

This is a trend that’s only set to grow. Remote working is on the rise, which has led to the accelerated adoption of collaboration tools – especially video. This means we’re all generating more data than ever before. So how do we make use of it all, exactly?

Caroline Lewis – sales director at workplace data analytics business Tiger – explores the power of insight in driving employee engagement and a positive office environment.

A fear of the unknown

When it comes to how an employee feels about data analytics, they usually sit in one of two camps – they either love and embrace it or they’re really wary of it.

But no matter which side of the fence they’re on, their chosen stance often stems from how business owners have communicated the concept with them in the first place.

Those who are more ‘on board’ tend to have been informed about the ‘how’ and ‘why’ behind its implementation – hearing how it can be used as a company-wide efficiency tool. Whereas, on the other side of the coin, those who are less familiar with its usage usually have a more negative perception of what benefits it could possibly bring to an organisation – believing it’s solely a mechanism for identifying job cuts or people who need to work harder.

And it’s this lack of clarity from management which gives way to this ‘Big-Brother-like’ cynicism.

Perhaps it’s because the term ‘data’ is commonly associated with ‘exams’ and ‘tests’, that we’ve naturally shied away from it – being fearful of the end result. Put this in a workplace context and the prospect of introducing data analytics into the fold can quickly make colleagues feel uneasy – especially if they’re left to wonder why it’s being applied.

With no steer or messaging from management, it’s easy to head straight down the avenue of negativity – worrying it’s because people are performing badly and it’s a tool to keep a close eye on staff performance.

However, this really isn’t the case. In fact, it’s quite the opposite.

Maximising efficiencies and empowering a workforce

When communicating what data can do, it’s important to stress its role in supporting and engaging colleagues with their day-to-day jobs, and that it’s not there to test or trick them.

The role of workplace analytics looks different for every company, as it’s ultimately down to what a particular enterprise wants to achieve. That said, on a granular level, it’s all about looking at bottlenecks within an organisation – promoting better use of collaboration tools both old and new, creating efficiencies, optimising staffing levels and improving KPIs. In addition, its purpose is to equip workers with the ‘evidence’ to make, or complement, informed business-critical decisions, that positively impact not only their department but the organisation as a whole.

However, the above is only possible if this data is made accessible to ‘the masses’ – aka the whole labour force. If dashboards are disseminated solely on a c-suite level, this is when it can quickly feel like results are being scrutinised and the data is nothing more than a surveillance instrument.

Instead, if everyone has oversight of the detail, they can see exactly what’s going on and utilise this knowledge to empower their team to make individual improvements which contribute to achieving a greater business-wide objective. And it’s when all employees have visibility over the enterprise’s performance, that a culture of trust and autonomy naturally develops.

What data organisations want – or need – a view of depends on what they’re keen to achieve. It could be anything from tracking how long call-wait times are, which employees repeatedly suffer with a lack of connectivity or technical issues, the seasonality of call volumes, or looking at whether or not more staff are needed and break times need staggering etc.

The possibilities really are endless, but what’s pivotal to remember is that when the intelligence is there acting as an ‘enabler’ – helping employees to carry out their day job more efficiently – engagement levels increase and everyone feels like they’re working towards one common goal.

The domino effect

Interestingly, if workplace data analytics are used in a transparent and collaborative way, this will also, by its very nature, lead to happier customers – and staff who feel fulfilled and proud of the job they’re doing.

It’s all one big cycle – one element cannot exist without the other.

That’s because detailed insights often highlight the pain-points or bugbears clients have too – no matter how big or small, such as long call-waits at a certain time of day. When this is identified and addressed, neither the workforce nor the customers have to deal with the other’s frustrations over a call or via email.

In short, when employees are engaging with clients for positive reasons, this quickly closes the loop and positively impacts company culture too. Workers feel less stressed, aren’t dreading awkward conversations, and feel empowered to confidently interact with their accounts.

Data for the future

Additionally, as a result of having more insight into how an organisation works, this allows teams to make more intelligent forecasts.

For instance, if managers can see what ‘issues’ are seasonal and which are day-to-day concerns, they have greater flexibility to adapt and make decisions for the long-term good of the business – instead of knee-jerk reactions.

Additionally, while real-time stats are useful, the value of analysing historic information shouldn’t be overlooked. Companies can learn from what is happening – and has happened – to ensure operations run as seamlessly as possible, with maximum employee engagement and productivity.

And it’s arguably this level of informed collaboration that forms the basis of any workplace which values and wants to retain its people well into the future.

Caroline Lewis About the author

With over 20 years’ experience in the tech industry, Caroline Lewis is the sales director at data analytics business, Tiger. She first joined the company’s customer support team in 1999 after achieving a BA Hons degree in computing and informatics, and it was her love of people and tech which soon saw her develop a keen interest in the commercial side of the business.

 

 


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Data analytics throughout COVID-19

Bingqian Gao, Data Science Lead at TrueCue

data, codingThe impact of COVID-19 has seen governments and organisations turn to data for their decision-making like never before, reflecting not only the increased importance of data, but also the speed at which senior management have come to recognise the insights which can be gained from harnessing it.

In only seven months, data literacy, collection and analytics has seen significant advancements, leveraged through increased quantitative information in the mainstream media informing and directing the public. Data analytics has also progressed in business contexts, helping employers to gain greater insights into their organisational needs, enabling them to target areas of struggle amongst the workforce and plan as much as possible for what remains a clouded future.

Because of this, now is the perfect time for reflection to better understand the role data analytics has played during the crisis and how adopting a data-driven approach can lead us into the next phases of recovery.

  1. Context is key

In order to leverage the true potential of available data, organisations must first make time to understand the context of the data that has been collected, whether it is system collected, reported or survey based. Raw data forms the foundation of any subsequent analysis and the quality of the data anchors impact the trustworthiness of the conclusions drawn. To put it simply, data that is collected from an unreliable source will have a negative impact on the overall analysis.

A significant example of an unreliable data source is the recent paper retraction scandal with The Lancet, which claimed and then retracted that using Hydroxychloroquine on COVID patients increased heartbeat irregularities and death rates. This had a devastating impact on the research and treatment landscape for COVID-19 and forces us to consider how many flawed analyses are out there.

To avoid error, once data collection has been grasped – bearing in mind there will always be some level of ambiguity – we must consider how to clean and process the data before analysis, and whether this places any implication to the interpretation and conclusions drawn. Ultimately, data-driven actions should be based on analyses that are scientifically rigorous and robust.

  1. Collaboration and speed to insight

Collaboration and speed to insight are critical when preparing for the unknown. As many have noted, the pace of change in the current climate is relentless, with organisations being compelled to make data-driven decisions within hours or even minutes. To minimise the risk of missed opportunities, swift action must be taken before the value of data diminishes.

At present, economists are taking high frequency or real-time data such as job postings and weekly unemployment claims as guidance. This must continue going forward, with organisations, healthcare services and government bodies sharing suitable data sources and making informed decisions based on insight from data they have now.

  1. Machine learning or scenario modelling?

Throughout the past seven months, many have wanted to utilise the power of machine learning to elevate their organisation from basic level descriptive and diagnostic analytics, to complex predictive or even prescriptive analytics. This not only enables employers to take immediate action, but also helps them to ensure preparations can be made for the near and mid-term future.

However, unprecedented events like COVID-19 have meant many organisations have been forced to take a step back and re-evaluate their approach. The idea of machine learning is to let the machine learn from existing or historical data. The validity of the approach is challenged when there is not enough historical data or past patterns to learn from.

To overcome this issue going forward, there are two viable solutions. The first is to stick with machine learning and use other historical events as a proxy. The second is to consider alternative techniques such as scenario modelling, which is a process of examining and evaluating possible future outcomes. Either way, finding new ways to conquer data and model the unknown will be critical in the coming months. 

  1. Data visualisation does not equate to interpretation

Data analysis and visualisation skills have been largely democratised, with desktop software such as Tableau widely accessible. Yet, in spite of the explosive amount of quantitative information in the mainstream media, data literacy is not just about creating charts and graphs.

Analysing data – apart from cleaning, transformation and visualisation – means interpreting the results and using this to accurately inform operational decisions. The key takeaway here is that visualisation does not equate to interpretation and storytelling, which often requires industry knowledge.

  1. Data drives actions

And finally, analyses should always result in data-driven insights that inform business actions. After data is collected, cleaned, analysed and presented in an accessible manner, it is important that analytics teams are thinking about what comes next and how businesses should act on the insights and better prepare for the future.

The use of data during this time has been critical to our survival, helping organisations, healthcare services and government bodies to mitigate the challenges brought about by COVID-19. If this progression continues – with innovation, speed and collaboration playing a lead role – there is every chance we will continue on this road of recovery and survive or even thrive in the challenging times ahead.


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Better for everyone: how data analytics can transform workplace culture

office, workplace culture

By Elen Davies, Director of Expert Services, Temporall

Phrases like ‘workplace culture’, ‘organisational health’ and ‘high-performance culture’ have recently become common in boardrooms as companies look to mimic the success of companies with high-profile cultures like Google and Asana.

These organisations share one crucial trait: they know that in a highly competitive marketplace, culture can provide an advantage. It helps attract and retain high-calibre employees, impacts organisational performance and boosts the bottom line.

But if high-performance culture is so important, exactly what is it, and how can companies make sure they have one?

What is a high-performance culture?

Workplace culture is not just about making sure staff are motivated and treated fairly - it goes deeper, explaining how employees behave and make decisions on a daily basis.

Culture is best defined as the values, behaviours, processes and systems in an organisation that decide how work really happens. A company’s values and ideal culture might be defined by the leadership team, but it is how these play out in the day-to-day behaviours of all employees that really shapes the workplace culture.

There are a few obvious things people look for in a company culture. We all want to work in a place where people are treated well, where leadership cares, and where there are great benefits. But having a good culture isn’t about gimmicks or short-term motivation boosters like beanbags and free sushi. It’s about how the organisation actually works day-to-day, and how well people’s actions are aligned with the business’ overall strategy and identity. It has a significant impact not just on how happy and efficient people are at work, but also on the company’s overall performance and success.

The future of culture: analytics

So, how do you know if you have a high performance culture or not? Culture analytics is technology which makes it possible not just to measure and understand your company culture, but to make changes and track the effect they have.These cutting-edge tools can measure the previously unmeasurable, turning data into insight that helps leaders take informed action.

Data analytics is already a growing practice in HR. By collecting data about payroll, absences and operations performance, it gives insight into an organisation’s workforce and HR practices. So imagine the questions that could be answered by technology gathering more complex data about every element of company culture.

  • Is our culture evolving to support our strategic goals?
  • Which members of staff have the most social capital, and why?
  • Do our staff understand what our values are and are their behaviours and actions in line with them?

These are the kinds of questions culture analytics can answer. Not only does it mean that culture can be measured so accurately that it could become the latest KPI, it can even use artificial intelligence to predict future trends in the business.

Early analytics adopters

Sophie Berryman, VP Talent and Organisation Development of Rakuten Marketing, is an early adopter of culture analytics. She says ‘We have moved away from a narrower focus on engagement towards a more dynamic and strategic focus on culture analytics. We are asking the right questions, which are backed up by behavioural analysis and psychometrics, and we have the right tools to analyse and truly understand that data.’

The ultimate goal for any businesses should be to align culture to strategic objectives. a  And the way to measure and track this accurately and continuously is through Culture Analytics

But it’s not just businesses that benefit. Measuring and improving a culture is best for staff too. With the kind of high-performance environment that culture analytics can provide, employees will know what they’re aiming towards and why, feel trusted to go and make it happen, and be highly motivated to go and achieve it.

Elen DaviesAbout the author

Elen Davies specialises in helping individuals and groups shift how they think and behave. She brings more than 15 years senior level consulting and Board level experience to Temporall along with her passion and depth of experience in coaching, psychology and behavioural change.

A seasoned executive coach, communications and employee engagement consultant, she is dedicated to supporting individuals and organisations access their full potential. Elen integrates psychodynamic and humanistic approaches and she has also studied with the leading thinkers in the field of developmental psychology.