Building Your People Analytics Blueprint

A Step by Step Guide through your journey

Photo by Boxed Water Is Better on Unsplash

In today’s world of data, that technology seems to be growing every second, we need a road-map to navigate transformative shifts.

If you’re in charge of a new People Analytics team or considering where to channel resources, you might be thinking: “How can I truly harness this?”

But, like any puzzle, to see the bigger picture, we need a plan. We need to know where to start, where we’re headed, and the pieces we need along the way. In the following sections, using simple steps and practical advice, I explore how to set up a People Analytics journey that truly shines.

But first, let’s understand again the ‘Why’ before the ‘How’. Why is People Analytics so crucial?

People are at the heart of any organization. They’re its pulse and its driving force. When we talk about People Analytics, we’re essentially talking about tapping into this pulse, deciphering its patterns, and using those insights to make it thrive. It’s about understanding what drives your team, their motivations, the challenges they face, and creating an environment where they can do their best work.

People Analytics isn’t just about data; it’s about harnessing this data to enhance the employee experience, leading to improved business outcomes. When teams are understood and supported, they become more productive and engaged, translating into growth and innovation for the business.

So now if we are in the same boat, let’s start the journey step by step as follow:

Step 1: Our Starting Point, The Power of Analytics Maturity Assessments

Starting any journey with clarity is crucial. Now, in the field of People analytics, this clarity is achieved through something called a People Analytics Maturity Assessment.

Think of it as a health check-up but for your HR analytics journey. It helps you gauge where you stand in terms of data capabilities and readiness to use advanced tools for your HR data.

Why is it important? Just as doctors need to understand a patient’s history and current health to prescribe a course of treatment, People Analytics leaders need to understand their organization’s analytics maturity to chart the right course forward. This assessment evaluates various facets — from your current technological infrastructure and team capabilities to your strategic alignment. And just like a doctor’s visit might show areas of improvement, this assessment can spotlight areas where you can bolster your analytics muscle. By recognizing these aspects, we not only map our starting point but also gain insights on potential growth areas.

Step 2: Dreaming Big, But Starting Small: Understanding Goals

Envisioning our future requires us to not only dream big but also to segment our dreams into actionable steps. Let’s understand this with a breakdown of goals:

Short-term Goals: These are the immediate targets, usually set for the upcoming weeks or months. They provide quick wins and momentum to drive the team forward.

• Example: Implementing a new feedback mechanism to understand employee sentiment by the end of next month.

Short-term goals give teams early successes, instill confidence, and provide tangible results that can motivate and propel them towards mid-term and long-term goals.

Medium-term Goals: Set for a horizon that spans from six months to a couple of years, these goals bridge the gap between our immediate targets and our grand vision.

• Example: Based on the feedback mechanism results, designing a comprehensive training program to address skill gaps in the team over the next year.

Think of these as milestones. While the journey might be long, medium-term goals offer checkpoints of progress, ensuring the ship remains on course. They allow for periodic assessment and course corrections if needed.

Long-term Goals:

These are our beacon, the lighthouse guiding our journey. Set for several years down the line, they encapsulate our grand vision for our analytics initiative.

• Example: Developing a predictive model in the next five years that forecasts talent needs, aligning them with market trends and business growth projections.

Every sailor needs a North Star, and long-term goals are ours. They provide direction and ensure that every short-term achievement and medium-term milestone contributes to realizing our grand dream.

Aligning our team with a shared vision, segmented into these goal types, ensures that everyone aboard understands the journey ahead. It helps in setting priorities, assigning resources, and measuring progress. Whether we’re celebrating the achievement of an immediate target or toiling towards our grand vision, every step taken is in sync, moving the ship steadily towards its destination.

Step 3: What’s In Our Toolkit? Taking Inventory of Our Data Resources

Our journey through the analytics is powered by data. Just as a carpenter assesses his tools before crafting a masterpiece, we too must know the data sources at our disposal and their quality:

What is our existing HR Data:

This is often our first go-to. It encompasses metrics like demographic data of people, attendance, performance evaluations, and training records. These data points can offer rich insights into workforce productivity, skill gaps, and areas of improvement.

Financial Data:

This can include payroll data, compensation structures, benefits disbursement, and other financial metrics related to our workforce. By understanding our financial landscape, we can better gauge the return on investment for various HR initiatives, ensuring fiscal responsibility while aiming for high impact.

Feedback & Surveys:

Direct input from our employees, whether through annual surveys, feedback forms, or informal channels. There’s no substitute for direct voice. This data helps us understand employee sentiment, aspirations, and areas of concern directly from the horse’s mouth.

External Data Sources:

This might include industry trends, competitive benchmarks, and other data from the broader market. To steer ahead, we need to look beyond our own ship. External data gives us context, helping us understand our standing in the broader industry landscape and identifying opportunities or threats on the horizon.

We need a clear, comprehensive inventory of our data sources. It aids in strategizing our journey, ensuring we’re leveraging all available assets and can make informed, effective decisions. Knowing what we have in our toolkit is the first step in crafting impactful, data-driven strategies.

Step 4: Navigating Challenges, Identifying and Prioritizing Pain Points

Every journey has its challenges, whether it’s unexpected storms or unplanned roadblocks. In our People analytics voyage, these are our organizational challenges and pain points. Identifying them upfront ensures we’re not caught off-guard. Some of those challenges in people-related topics that many companies suffer from are as follow :

1. High Attrition Rate: A common challenge where businesses see a faster-than-desired turnover of employees. High attrition often signals deeper issues, from unsatisfactory work conditions to misaligned company culture. Plus, frequent hiring and training can be costly.
2. Lengthy Recruitment Process: When it takes too long from identifying a vacancy to filling it with the right candidate. Longer hiring processes can deter potential candidates, leave teams understaffed, and result in lost productivity and opportunities.
3. Skill Gaps in Existing Talent: A mismatch between the skills your team has and the skills your projects need. Without the necessary expertise, projects can stall, or results may not meet desired standards. This also hints at potential upskilling or training needs.
4. Low Engagement Levels: When employees are not emotionally committed or passionate about their roles. Disengaged employees can impact productivity, innovation, and overall workplace morale. They’re also more likely to leave, contributing to higher attrition rates.

Now, while all these challenges matter, we can’t tackle them all at once. That’s where prioritization comes in.

By collaborating with stakeholders, we can weigh each challenge based on its impact and urgency. For instance, if the high attrition rate is draining resources and hurting team morale, it might be flagged as a top priority.

Once we have our list prioritized, it’s essential to dive deep into the top challenges. Using our earlier example, if high attrition rates top the list, we might delve into exit interviews, feedback forms, and workplace engagement surveys to root out underlying causes.

Understanding and prioritizing our pain points is like a ship’s captain studying the weather forecast before a voyage. It equips us to handle storms, ensuring smoother sailing and a higher likelihood of reaching our destination successfully.

Step 5: Aligning Tools with Challenges, Matching Data to Pain Points

Think of this as fitting together the pieces of a puzzle. Now that we’re familiar with our tools (data) and the challenges at hand, it’s time to find the right data to address the specific hurdles we face. The challenges you’ve identified, such as high attrition rates or lengthy recruitment processes, are pivotal. But equally important is having the right data surrounding these challenges.

Imagine trying to solve a mystery without all the clues. You might make some progress, but you’re likely to miss the full picture. Similarly, to address the challenges in your People Analytics, you need all the relevant data points. This helps in two primary ways:

1. Insightful Analysis: With comprehensive data, you can go deeper, uncover patterns, and draw meaningful conclusions. For instance, if you’re looking at high attrition rates, data on exit interviews, employee engagement scores, and internal mobility can provide a holistic view.
2. Strategic Action Planning: Knowing what data you have in place sets the stage for your next moves. It’s the foundation upon which you build your strategies. If you’re informed that a significant portion of employees are leaving due to a lack of growth opportunities, your actions would be different than if they were leaving because of workplace culture issues.

So, as you explore the challenges, simultaneously map out the data sources you have, assess their relevance, and identify gaps. It’s a meticulous process but think of it as gathering all the tools you need before setting out on an expedition. By ensuring you’re equipped with the right data, you’re already several steps closer to your destination.

For instance if you want to evaluate the Low engagement rate of your people, you should try to find these relevant data: Employee satisfaction surveys, feedback from team meetings, participation in voluntary company activities, and engagement metric tools (like eNPS scores).

Assessing these data points can help pinpoint what’s working and what’s not in terms of keeping employees engaged and motivated.

But here’s a twist: Sometimes, you might realize you’re missing the data you need. Let’s say you want to address attrition, but you don’t have comprehensive exit interview data. This gap isn’t a dead end , it’s an opportunity! It signals the need to enhance data collection methods in that area, ensuring that future analysis is richer and more informed.

Drawing the right data to address specific challenges is a must. While the outcome of your analytics models is only as good as the components that go into them. Ensuring alignment between data and challenges ensures that our strategies are relevant, actionable, and impactful.

Step 6: Prepping for the Main Event, Data Preparation and Cleaning

If data is the main ingredient of our analytics dish, then think of data preparation as the meticulous process chefs go through to wash, peel, and chop their ingredients. It’s a crucial step to ensure the final dish (or in our case, insights) is palatable and meaningful:

Addressing Missing Data: Sometimes, crucial pieces of data might be missing from our dataset, leading to incomplete analysis. Like missing a key spice in a recipe, missing data can skew results. Addressing these gaps, either by imputation or sourcing the missing data, ensures a comprehensive analysis.

Removing Outliers: Outliers are extreme values that can potentially distort our analysis. They can sway our insights, leading to inaccurate conclusions.

Standardizing Data Formats: Different data sources might record similar data in various formats. For instance, dates might be in MM-DD-YYYY in one source and YYYY-MM-DD in another. Consistency is key. Standardized data ensures smoother and more accurate analytics processes.

De-duplicating Records: Redundancies in our dataset can often creep in, especially when merging data from various sources. Duplicate data can inflate results, making insights less reliable.

But, what if upon inspection, we realize our data is not meaningful enough?Don’r worry! Recognizing gaps in our data or issues in its quality is half the battle. We can then strategize on either sourcing the required data or tweaking our analysis methods to accommodate these gaps.

Data preparation, though tedious, is a cornerstone of good analytics. It’s a transformative process, turning raw, unruly data into refined, ready-to-analyze information. Like chefs who swear by meticulous prep work for a delightful dish, analysts know the value of thorough data preparation for deriving actionable insights.

Step 7: Delving into Data Analysis

Now that we’ve gathered the right data, let’s get our hands dirty. But where to start?

Choose Your Tools Wisely: By knowing your data landscape and the current vision, you need to select the right analytical tools for your data. This could range from basic Excel analyses for smaller datasets to using more sophisticated tools like SAP Analytics Cloud, Python or R for larger and more complex data.

Seek Patterns and Correlations: Perhaps employees with longer commute times are more likely to leave the company, or maybe there’s a strong correlation between those who participate in professional development programs and those who get promotions.

Iterate and Refine: Rarely does the first pass at data analysis provide all the answers. You’ll likely need to go back, adjust your approach, ask new questions, and dive in again.

Collaborate with Others: Sometimes, a fresh set of eyes can spot something you missed. Collaborate with the stakeholders to get diverse perspectives.

Document Your Findings: As you uncover insights, document them. This not only helps you track your progress but also makes it easier when presenting your findings to decision-makers.

Remember, the goal isn’t just to gather information for the sake of it. It’s to extract actionable insights that can guide the organization’s strategies and decisions. As you dig through your data, keep the larger objective in mind and ensure that each step you take brings clarity and value to the organization’s goals.

People Analytics isn’t just a buzzword; it’s the compass guiding modern businesses. Like the heartbeat of an organization, it reflects the vitality and essence of its workforce. Diving into this area is necessary to unlocking the secrets behind a company’s most valuable asset: its people.

But I know that navigating the world of People Analytics can sometimes feel overwhelming. And remember, you’re not alone on this journey. If you need a helping hand or some guidance along the way, don’t hesitate to reach out. I’m here to help, ensuring your endeavors in People Analytics are both productive and enlightening.

Thanks for reading, Follow me for more content, Stay fresh, be nice! :)