People analytics has become a VERY big deal!
There has been a seismic shift in the way managers and directors view people analytics. It is no longer relegated to the nearest HR manager or seen as fluffy metrics. The scope has broadened from employee engagement, retention and learning. It now includes business problems like:
- Sales productivity
- Talent management
- Workforce effectiveness
- Workforce planning
- High-potential retention
- Fraud
- Accident patterns
- And much, much, more.
Companies are now reinventing technical analytics and creating powerful new enterprise analytics solutions. This new breed of digital solution is driving change as companies can now get real-time analytics at any given point within a business process.
This allows for a deeper understanding of issues and challenges the business and its workforce face.
While a staggering 71% of companies see people data as a top priority, the execution has been less than convincing.
There are several reasons why the implementation of people analytics has been poor.
But, that’s for a separate blog.
Our aim in this post is to take a closer look at using a human-centred data-driven approach to create and build a high-performance culture.
Simple.
So in the immortal words of Chauncey Depew, “The first step towards getting somewhere is deciding you aren’t going to stay where you are.”
And on that note…
Step 1: Get the right data
You can’t change what you don’t measure or what you measure incorrectly.
To be able to effectively implement the new data-driven strategy you need to ensure that you are able to collect data from a wide variety of touch points in real-time.
It is essential to gather data from as many data points as possible to get the full picture and ensure you aren’t missing anything. It can be easy to overlook smaller more seemingly insignificant data points but in time even the smallest of data points tells their own story.
Layered on top of this vast array of new data you have coming in, are four crucial elements:
- Accuracy
- Security
- Privacy
- Consistency
These four elements form the basis of what is considered good, reliable data which can then enable business decisions.
Step 2: Listen more than you talk
The old adage that good managers listen twice as much as they talk, is also true for the companies where they work.
In a previous blog, we spoke about the end of the annual employee survey. It is well and truly dead.
There are however a wealth of established tools companies can use to build effective listening frameworks which include pulse surveys, engagement surveys, performance reviews and the list goes on.
The chart from Deloitte’s “High Impact People Analytics” study, shows the percentage of organizations using various listening channels to collect data.
And then there are the new kids on the block.
Innovative high tech solutions like data gathered from wearables, natural language processing tools, internal social media (bountiXP, Yammer) and external social media (Glassdoor), are becoming more widely available.
Artificial intelligence has progressed to the point where you can now analyse video interviews and assess the candidate for honesty and personality. Crucial, when trying to recruit top talent.
Companies have started to play around with new data sources to help them get a better understanding of their employees.
Finding the right mix of listening tools to gain feedback and actionable insights is an important step towards creating a high-performance culture.
Step 3: Data literacy for all
It is easy for most companies to focus on building and enhancing people analytics skills within the core team that is meant to be in charge of it.
But, you’d be missing a big opportunity.
Enabling basic data literacy within your company, specifically, HR staff is very important.
That does not mean every staff member should become proficient at running regressions or structural equation modelling. But rather that they understand the basics like:
- Representative samples
- The difference between causation and correlation
- Statistical significance
- Being able to manipulate a data set
- Use simple parameters
- Understand relevant data sources and formats
Developing an analytical way of thinking is extremely valuable within a company. It means that not only will more people be asking questions but they will be more likely to be asking the right questions.
Learning is a crucial function of most high-performance companies and with platforms like Udemy, GetSmarter, and Skillshare, data literacy courses are more widely available than ever before.
Step 4: Diversity matters
The core responsibility of anyone dealing with people analytics is mostly focused on influencing and communicating the data and insights.
This is only truly possible if the team possesses a diverse range of skills and deep organizational connections. These two aspects will ensure that the data and intelligence are comprehensive and not merely one-sided.
It will also ensure that the data is effectively communicated to the right teams and departments and where it can most effectively be utilised.
Include people with strong connections within the business. These individuals focus on being the intermediary between the analytics team and strategic business units.
Their function is to understand the needs of the business, relate those challenges and objectives back to the analytics team and then ultimately provide intelligence from the analytics team back to the business.
Diverse teams build better solutions. If the data team only includes HR people you would be right in thinking that all the intelligence and insights will be heavily HR focused.
By building a diverse team that includes people with expertise in sales and marketing, operations, IT, HR, finance, consulting, and organization psychology you will ensure that the data is more holistic and should provide relevant intelligence for a wider variety of business challenges.
Step 5: Scale data delivery
“If a tree falls in a forest and no one is around to hear it, does it make a sound?”
We are not about to dive into a philosophical thought experiment that raises questions regarding observation and perception. It does however raise a valuable point when considering our data delivery.
If you have the data analytics skills, and the listening devices are capturing a multitude of data points but it is not easily accessible or delivered to the right person at the right time, then does it matter if the data exists?
The ability to deliver data quickly, to a broad audience, frequently, for every decision is perhaps just as important as the four previous steps combined.
Scalable data delivery can take a few forms but the most popular are:
- Automated dashboards – Provide real-time data on predefined dashboards. This could include high-level data across the entire company or more granular insights in specific departments.
- Shared services – Shared service centre data connects the entire enterprise—employees, vendors, customers, and partners.
- Self-service – Allows business users to manipulate data to spot business opportunities, without requiring them to have a background in statistics or technology.
Scalable data delivery has many benefits. Firstly, it allows more data to be included in the decision-making process, which in turn leads to better decisions being made.
Secondly, it frees up the analytics team to focus on more complex business challenges like improving sales performance or reducing staff turnover in the call centre.
Step 6: Align business and analytics
“Far better an approximate answer to the right question, which is often vague, than an exact answer to the wrong question, which can always be made precise.” – John Tukey, Author of “The Future of Data Analysis”
Asking the right question at the right time is critically important in driving business success. The challenge in many businesses is that people analytics is rarely included in more complex decision making processes.
There is a gap between the challenges the business is facing and the solution people analytics has, and it needs to be closed.
In order to close that gap, there are a few things businesses could do:
- Don’t get stuck in the weeds. Work with departments and managers to identify the problems that are more relevant and pressing to them.
- Be proactive about providing data to business leaders. Don’t focus solely on their requests. If a certain data set is relevant be sure to get it into the right hands while it can still be of use.
- People analytics is not just for human resources. Make the jump from what can be perceived as fluffy people metrics to big data helping the business grow smarter.
Step 7: Embed data analytics into your culture
In this final step, we need to look past the confines of the data team and instead look holistically at the company culture. How is the data being used?
Does the company use data to truly drive decisions or merely use it as an afterthought to justify decisions?
A company with a data-driven culture is heavily data-driven and does not make recommendations or offer solutions that are not underpinned with sufficient data. Decision making is objective, scientific and evidence-based.
Creating a data-driven culture is certainly no small feat and often requires constant communication from senior management about the importance of data-driven decision making.
It is also an enabling environment that promotes experimentation. New tools, models, analytics methods, A/B testing and data segmentation all go a long way to embedding data in every tier of the organization.
An enabling environment and consistent communication from senior leadership is the perfect incubator for developing a data-driven culture.
With these seven steps in place, developing a high-performance organisation enabled by people analytics is simply a matter of time. The more integrated the data and the more experimentation that occurs will ultimately determine the final outcome and how ingrained it becomes in your company culture.
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