When it comes to people analytics, success means not having to second guess your process.
You should embark on this journey armed with the knowledge of best practices. But you should also have proactively researched the common pitfalls to anticipate the challenges that may arise. This way, you are fully prepared.
You understand how genuinely beneficial data-driven decision-making can be to the bottom line, the employee experience, and the organization's overall success. You know how much is at stake, so you want to get the best advice.
According to Dawn Klinghoffer, Head of People Analytics at Microsoft, “In its simplest form, people analytics requires good data, solid analyses, and effective processes.”
Here we add “solid strategy” to that list of ingredients and suggest twelve steps to success that will improve the quality of each of the four elements regardless of the stage of maturity of your people analytics journey.
1. Get executive sponsors on your cheerleading squad.
Getting executive buy-in to invest in people analytics is one thing. Getting committed, ongoing support that drives action is another.
Somewhere in your organization are one or more senior executives who understand the value of analytics. Seek a leader to be your champion and cheerleader—one who can articulate the vision of a data-driven organization.
2. Start by defining a business problem you need to address.
Thanks to the runaway successes of giants like Google, Amazon, and Microsoft, many organizations want to get on the bandwagon and copy their example.
But without adequately defining the problem you need to address and the questions you need answers to, you are setting yourself up for failure.
People analytics can benefit any organization, but another company’s success will probably not fit your problem. So, start there and identify the central question that will guide your process.
3. Lay a strong data foundation.
Think of your data as the foundation for your analytics and insights. You want solid insights from sound data, insights that your decisions can stand on.
Your data governance is critical for reducing risk by creating a single version of the truth.
A robust data foundation also means your data must be trustworthy, organized, and accessible. And it must be secure—adhering to strict privacy and ethics policies.
4. Create a data-driven culture.
Your organization’s leadership has to take on the role of change agent.
If you embrace and consistently model the reliance on data-informed decision-making that you want to engender within your organization, the rest will follow. Processes will have to be adapted, and mindsets changed over time but don’t sweat it. The goal is to create an environment where management no longer thinks that acting on instinct alone is an acceptable way to operate.
5. Democratize data.
Anyone who needs data should have access to it and the ability to understand and use it. It’s a brand new day when the IT team is no longer the gatekeeper of people data. #nomoresilo.
One way to democratize data is to use embedded analytics to put valuable data in the hands of users so they can make decisions and derive insights quickly and easily. Making data available to your managers increases their efficiency and empowers them to use it in decision-making.
6. Prioritize data governance.
Your data is a precious commodity. You must take your data stewardship seriously for regulatory compliance reasons and build trust within your organization and those customers, clients, and suppliers within your scope of operations. If you carefully define and manage data storage, access, and usage, you will uphold transparency, accountability, security, privacy, and ethics. It will boost your reputation and efficiency and reduce risk.
7. Keep your strategy and efforts aligned with your business goals.
If you never need to recalibrate, you’re doing it wrong. Continually measure the business impact of your people analytics efforts to keep on track and to make progress tangible. Ask yourself, will this analysis contribute to the business? Special projects are based on their value to the organization instead of what might be a manager’s pet project or a mere curiosity.
8. Create a cross-functional people analytics team with critical skills.
You’ll need a visionary leader or sponsor, data science and analyst skills, and someone who can translate data insights into actionable insights and deliver them to the executive. You also need input from Finance, Marketing, and the leaders of your various business lines as stakeholders and beneficiaries of your people analytics efforts.
9. Use SaaS. Cloud-based is the way to go.
You cannot beat the benefits of SaaS for cost-effectiveness and convenience. The subscription model allows you to only pay for what you need for as long as you need it, with the ability to scale as necessary. Accessibility from any device anywhere there is an internet connection allows unlimited mobility. Automatic software updates mean no more hassle than doing it yourself.
10. Make your data tell a story.
If you’re not a data professional raw data is like a foreign language. Visualizations will turn it into a language of bars, charts, and maps that is easy to understand and can be quickly interpreted by users. Pay close attention to your dashboard design because it will determine how easily your visualizations break down complex information and communicate trends, patterns, and relationships.
Aesthetics count. If you want to get the most of your data, it has to be represented in a way that allows for quickly spotting insights, conducting high-level analyses, and communicating findings to the decision-makers clearly and concisely.
11. Focus on actionable insights.
Insights might answer a question or confirm a hypothesis, but they only really add value when they can provoke action to improve the business. If you uncover insights from your data but cannot act on those insights to improve business outcomes, your efforts are in vain, and your analysis is wasted.
The proper analysis begins with understanding which metrics are essential to the business, and that comes from having a clear data strategy. One way to ensure that you get actionable insights is to focus on trends over time and relationships between variables instead of the metrics themselves.
12. Be agile.
Don’t be afraid to make mistakes. Your process should include an iterative cycle of monitoring and evaluation so you can adjust your strategy and methodology when necessary. If something isn’t working or giving the results you need, change it. It’s that simple. This is how you maximize the value from actionable insights.
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