Perspectives in Analytics

Implementing Analytics is a lot like making pizza.   The end result is fabulous, a very yummy pizza with our favorite toppings.  But how we make that pizza, can vary quite wildly.  Even the ingredients we use can vary as do the toppings.

If the goal is our favorite yummy pizza, businesses have the goal of building an analytics program which represents their business model and their strategy.  These Key Performance Indicators (KPIs) can vary wildly, even for businesses operating in a similar market.  The KPIs are our toppings.  Pepperoni for some and others avoid the anchovies.

How we support those KPIs can be vary as well.  What type of dough do you like?  Do you make the dough from scratch or buy a premade dough?  What do we add to the dough for interest?  Basil?  The dough is our technology stack.  You can build something completely custom with anjular.js and d3.js or you can buy something off the shelf, like Google Data Studio or implement Alteryx and Tableau.  There are no right or wrong answers, just the best decision for the needs of your business.  Low-budget frozen pizza to high-end gourmet pizza cooked in a pizza oven, the flavors vary.

The best advice I can give is to consider the sustainability of any stack before implementing.  Knowing the complexity and amount of data will ever increase is crucial. Being able to modify reports and deploy new ones fast is key to success.  Don’t forget KPIs can evolve as well and need to be reviewed regularly.

Happy Pizza Making! Er… happy analytics developing?

 

 

Why Hierarchies of Data in a Business Matter

thData, business, sales, insights, and revenue are popular keywords found in abundance around the internet these days.  As a Founder of my own company, I can certainly understand the need to focus on such keywords in daily, weekly, monthly, and quarterly discussions.

But, as a Data Analyst, not all keywords are created equal for each role in the company.  Let’s simplify and break the business hierarchies down to three levels, which have a direct impact on how data can be used:

  1. Executives: The top of the chain that defines long-term strategy, implementation, and overall decision making.
  2. Manager: The mid-level staff responsible for action of strategy, interfacing between the needs to the subordinates and the Executive teams.
  3. Operational: The largest population of the business with the responsibility to make it happen by pushing the buttons, interfacing with customers, and carrying out decisions hour by hour.

This three tier pyramid of decision making in a business is streamlined to illustrate key areas that any serious Data Analyst should have Continue reading