It’s your first day at the new job, your Analytics degree still fresh off the press, and you’re ready to start moving the needle for your company. As an analyst, your job is to inform. In 2023, high-level business decisions can’t be made on a whim or based on simple hunches; we need the data. Your job is to collect and interpret massive deposits of data and provide decision makers with real insights backed by real data.

Here’s the problem. On Day 1, the company dumps their massive data warehouse into your lap and casually tells you “have fun” as they walk away. Needless to say, your stress levels just spiked. Even with your skills, knowledge, and practice with data, you don’t even know where to begin. Data in its rawest form is nothing short of a beast, and when you have millions of data points to manage, it can feel like you’re raising a house full of toddlers all by yourself—just with fewer dirty diapers.

Of all the questions running through your head, the loudest is probably “Where do I even begin?” or “How do I parse through millions of data points to focus on only what’s important: the holy grail that can drive my company forward?” To answer this, we need to talk about something called core performance.

What is Core Performance and Why Should I Care?

In the Data Analytics profession, core performance is the set of metrics or indicators that demonstrate your level of success. They’re the meat and potatoes of your operations, the helm of the ship that either keeps your company on track, or prepares you for a major course correction. These metrics are indispensable since data analysts act as the first line of defense against possible market shifts that can make or break the company. If it’s happening in the market, you can bet it’ll show up in the data first. If you think of the CEO as the king of the company, the data analyst would be the trusted advisor who’s always seen whispering into the king’s ear.

As you’ve probably picked up by now, core performance is kind of a big deal; it helps your company set performance targets and track their progress, it gives you red flags for areas of improvement before they become emergencies, and it helps give your company some direction toward their goals—much like a captain’s compass.

“So I understand why Core Performance is important, but how do I distinguish this from all the other data points floating around in the ether?” That’s a fantastic question. And as many of you know, the answer to all great questions is always: It depends.

In all seriousness, Core Performance can differ wildly from company to company. The spectrum of possible company goals is huge, and even a single company goal may change from year to year (or month to month!). While one company might treat their Sales team like royalty and every dollar they bring in as manna from heaven, other companies might see networking and building partnerships as a healthier long-term goal.

No two companies are the same, so no two data reports should be the same either. The sales-team-centric company may prioritize leads generated, customer acquisition costs, and value per customer as their core performance, while others might put social media impressions, partner sign ups, or manufacturing costs at their core. Just remember, a critical tenant of core performance is making sure you’re tracking the right metrics at the right time. Other examples you might want to consider as your core performance metrics include: revenue, profits, customer satisfaction, employee retention, and employee efficiency. The ultimate responsibility of the analyst is dissecting high-level company goals, and connecting them with the metrics that give the best picture of the goal’s completion.

By now, the question “Why should I care?” should be pretty self-explanatory, but just in case, we’ll sum it up for you: core performance is what informs the decision makers of your company where they’re headed and at what speed. Without these key metrics in place, data analysts will be left floating in a sea of data, grasping for whatever metrics can keep them afloat the longest. Accurate reporting is crucial to every business no matter what their goals are, and having the right core performance metrics in place gives management the ability to zoom out and drill down into all levels of company performance.

Through the Looking Glass: Telescope or Microscope?

One of the biggest benefits to using core performance metrics is that they can paint you a data picture through a variety of lenses, from telescopic to microscopic.

As most data analysts can attest, members of the executive team are frequently in need of reports, forecasts, and analysis in order to make their next move. Business strategy is often like a game of chess—if you want to win, each move must be carefully considered and calculated. You won’t get very far against someone who understands the game if you just move your pieces around carelessly (perhaps the reason why I always lose).

Just as a chess master might take a step back and look at the board as a whole, considering all the possible moves and how each scenario might play out, so should executives view their business from time to time. We’ll call this the telescope approach: focusing on the big picture and high-level factors at play, momentarily setting aside the small details that might cloud your view of the stars.

Core performance is essential to providing this zoomed-out perspective because if you don’t have the right metrics nailed down from the start, executives won’t be able to make use of your reports—or worse—you send them chasing a target that’s not in line with the company’s goals. Imagine looking through your telescope at a beautiful constellation, only to have your friend inform you that you’re actually looking at a couple of planes in the air.

The second important use of core performance metrics is the ability to drill down to the most specific details to make changes on the front lines, because as the visionary artist Vincent van Gogh once said: “Great things are done by a series of small things brought together.” We’ll call this the microscope approach: identifying concrete details that are either helping or hindering your company goals. Perhaps that’s an underperforming employee who needs extra guidance, or a sales process that’s becoming a bottleneck for other teams.

Having your core performance metrics in place and clearly identified allows executives and managers to better prioritize resources based on how closely a proposal is to the core metrics. For example, if improving employee retention is one of your top goals for 2023 and surveys have indicated that employees value a “fun workplace,” maybe shelling out for that foosball table takes priority over paying for newer and better software extensions.

The drill down technique allows you to solve smaller problems before they pile up into a company killer. With the right data from the analyst team, executives are better equipped to delegate tasks to various levels of management that will ignite change in the trenches of your business operations.

Not an Overnight Success

Unfortunately for many lightning-fast companies, a data analytics strategy takes time to build. You can’t expect a new hire such as the one first described to be able to revolutionize the company overnight. However, through implementation of core performance metrics, your company can strengthen its reporting process for more reliable, accurate, and—most importantly—helpful insights every step of the way.

But at this point, you may be asking yourself, “Is this really worth it? What can I actually expect to get out of a process like this?” which makes sense. Changing the way you think about data takes time, and having reservations about making that kind of commitment is normal. Let’s explore some of the benefits we’ve seen from companies who have risen to the challenge and focused their efforts into defining their core performance:

1. Increased revenue
   a. Increased customer lifetime value and reduced churn.
   b. More efficient sales and marketing processes.
2. A better support network and chain of command
   a. This is especially helpful for franchisees who rely on outside management for guidance.
3. Machine learning capabilities
   
   

Perhaps your eyes glistened at the word “revenue” or it was a combination of the three that excited you, but if you’ve gotten this far, that means you’d probably be willing to try something new with your data. While we can’t promise you’ll see results tomorrow, you’d be surprised how fast the following four steps will fly by when you’re motivated to make it happen.

Step 1: Establish Core Metrics for each department of the company

Did you think you were going to implement core metrics for a single department on its own? Think again! While core metrics can be useful for any team who takes advantage of them, they’re an absolute game-changer when applied across the board. When departments work together with the same structured goals in mind (or differing goals that complement one another) it’s easier for a unified vision to come into clarity, both within the data and in practice. Here’s a list of questions to ask yourself and other departments to help ensure core metric alignment:

• What metrics are you currently tracking and how?
• What data are you currently collecting?
• What are your company’s main goals and objectives?
• What metrics are your competitors using?
• How will you use the metrics in your decision making?
• Who is responsible for tracking these metrics?

Step 2: Establish Core Dimensions that describe the detail of each metric

Aside from the aforementioned metrics, don’t forget to choose your core dimensions carefully as well. These will help you filter your data more effectively, allowing you to see patterns and identify trends more quickly. Achieving the level of granularity that best fits your company’s needs is important. Granularity refers to the specificity of each dimension you’re collecting, such as time, deciding to track year, date, or date and time. Identifying the ideal granularity is a delicate balance; greater detail comes at the sacrifice of simplicity, so choose wisely. If it’s not feasible or necessary to collect certain data every minute, for example, then it may suffice to just track the date.

Step 3: Combine, & transform source tables into a centralized data model

As Benjamin Franklin famously puts it, “Everything has a place, and everything in its place.” The same goes for data. A disarray of source tables will make your job a living nightmare, so the process of transforming and cleansing your data is crucial.

• After choosing your level of granularity, transform and cleanse your data to be uniformly compatible with your centralized model. Analytics Odyssey can help with this.
• This may involve aggregating data to a higher level of granularity to ensure the data mapping corresponds with a common set of dimensions.
• KEEP YOUR DATA MODEL ACCURATE AND UP-TO-DATE. Yes, I’m looking at you. In order to stay reliable and useful, you must monitor and test data quality regularly.

Step 4: Create a dashboard where core metrics match KPIs

In your dashboard, input your core metrics as KPIs along the top bar, allowing you to keep track of them all in real time. Never miss a beat: this kind of dashboard integration allows you to always have your hand on the pulse of the company. We know finding the right dashboard tool is hard. Thankfully, Analytics Odyssey can help with that too!

Here’s an example to get you thinking

A dashboard like this turns you into a data superhero. With the ability to filter all your data by specific decisions, you can save brainpower to put to finding real solutions instead of searching for the most important data pieces like needles in a haystack. Here, everything you need comes at the click of a button. Want to find sales volume by location? Click, done. Want to see a table of your sales over time? Click, click, “your table is ready, sir.”