Data based decisions is one of the biggest keys to success in business today. The Wall Street Journal ( here
) identified highly functioning Business Intelligence (BI) as a key competitive factor that will enable companies to dominate their competitors way back in 2012. Fast forward 7 years later, and companies have spent billions in data, analytics, BI and are now starting to spend massive money on Big Data ( here
).
So Data and BI is a big deal. Businesses get it.
Or do they?
After talking about data and analytics to businesses for a long time, it's still very obvious that this is a totally new field to most people. If you don't work in data, the whole thing can be difficult to understand.
As a data professional, and someone who analyzes everything (a big sorry to my wife...) it became obvious as to WHY business partners do not understand data.
HISTORY
Classic business professions have been around for thousands to millions of years. These professions have been woven into our collective society and education systems. Accounting has been around since Mesopotamia ( here
), Sales predates Accounting, with the very oldest being Toolmaker dating back 2.6 million years ago.
Data and analytics is a profession in it's real infancy. SQL was first described in 1970 ( here
), became an ANSI standard in 1986, and has been going through massive change ever since. Relative to other professions, data related positions is insanely new to everyone.
EDUCATION SYSTEM
In my MBA program (just over 10 years ago) data and analytics received a single line in a single business textbook 'Data analytics is an exciting new field that should be monitored for growth by business professionals'. Even the two classes in Statistical Analysis talked far more about the math than how data and analytics could be used in every day situations. While I loved these classes, most just got through the stats courses and look on stats as something for the 'nerds'.
Quickly browsing the local Universities graduation requirements for a degree in Business, looks like things might be improving slightly with optional courses in Business Intelligence, Data Base Management Systems and System Analysis and Design. Yet even today these basic analytics courses are still optional for business school graduates, unlike accounting, finance statistics.
EVERY DAY LIFE
Everyone knows hundreds of professions that they work with and interact with every day.
Doctors, lawyers, accountants, car salesmen, police, fire fighters... heck, baristas (a relatively new broadly held job- thank you Starbucks) are well understood professions that people see in their every day life. Even programmers and help desk agents have entered the realm of people that people have become accustom to interacting with.
Yet no data analysts or data scientists in the mix...
POPULAR MEDIA
Our favorite characters in TV and movies have positions that we can relate to and understand. There are hundreds of doctor, lawyer or cop dramas. 'The Office' is the #1 show on Netflix. Think of a job, you can easily imagine a favorite character with that job.
Who do we have in Data Analytics?
Can you think of one?
No- none of the guys on Big Bang Theory are data analysts or data scientists.
I've only found one.
Chandler Bing on 'Friends'.
Yep. That's the one and only analyst in modern culture.
NO WONDER
No history with data. No education. No personal connections. No popular culture. No wonder people do not understand data. It would be unreasonable to expect people to understand data analytics, data science, Business Intelligence or data engineering.
REAL WORLD RAMIFICATIONS
This lack of understanding has some very negative real world ramifications. From the Cambridge Analtytica data scandal ( here
) to every day interactions with people in business, not understanding how data works can cause real harm.
The very first data analytics project I ever worked on was to find the tellers within a bank that exhibited a behavior that was thought to be 'gaming' the bonus system.Unlike the Wells Fargo account fraud scandal ( here
), the bank I worked for watched very closely to ensure that no one in the bank was doing anything unethically.
Unfortunately, I was not tasked with finding people gaming the system who exhibited a type of behavior.
I was tasked with producing a list of employees who exhibited a given behavior.I was not given, and I was too new to ask, 'why' I was getting data.All the business user wanted was the employee name, and a number of events.
As a very new analyst I wanted show how efficiently I could obtain this information. I ran a few queries, did some validation, copy and paste into excel and some formatting quickly generated the list of employees who exhibited the given behavior. The file was then sent over to my business partner.
Two days later, the business partner called me to thank me for the quick work. Only at that point did he explain to me the 'why' they wanted the data. He informed me that the top people on the list had been gaming the system to get a bonus and that he had already started the termination process with HR. My quick work had 'saved the bank' from these unethical actors.
Or so he thought.
Once I understood the real end goal for the request for data, I understood how the request was fundamentally flawed. Several of the employees at the top of the list were part of a student education program where the bank gave students $25 to open a checking account to teach them how banking worked.
These employees were going to be fired because they participated in a student education program, and this director didn't understand the data.
Fortunately, I was able to explain this to the director, the termination process was paused, and we were able to sort through the list of people and find the true bad actors, and save many good people.
Bad guys were caught. Good guys were saved. Whew.
CALL TO ACTION
Until Chuck Lorre makes a popular hit TV show about data scientists, or HBO comes out with a data analytics late night comedy (man... I would watch BOTH of those) people working with data need to do something.
So what are we to do? How do we help bring data into the cultural norm? For that matter, how can we help our business partners better understand the complexities around data?
As someone who is very analytical, I understand that it is often more comforting and easier to work as a solo contributor or to only work with other analysts. This is mentally far easier and more engaging.
We need to break out of this mold. We need to get out and talk with our business users. Encourage them to dig into data. Show them the new tools that make data analysis and access data much easier.
KEEP IT SIMPLE
DEAR GOD- don't make it too complex for them. Most of them were thrown into Stats classes where they struggled to use R or perform other calculations. They saw this and ran away screaming.
Start with something familiar and easy for them to work with.
Excel and Power BI excellent starting starting points for these conversations. Excel has been out since 1985, and has been used by nearly everyone in business. Enhancing Excel skills and extending to Power BI is very easy and has a well laid out path.
Power BI and Excel Guided Learning ( here
)
Power BI and Excel; More than just an Integration ( here
)
What is Power BI ( here
)- for people new to Power BI
Get our partners working with Data. Get them using it in their day to day lives. Start them with Excel. Then move them into Power BI.
Once people start to get comfortable with data, then look at new tools like Databricks ( here
) for starting their journey into big data.
But that's a whole different blog post.
