Fact or Fiction: ANYONE can be an Analyst
Architecture and Technology: Modernise the FoundationOn 20 and 21 February, Nugit was proud to be part of the Gartner Data and Analytics Conference as a Cool Innovator. The event held true to its promise of being a dynamic and informative platform for industry leaders to connect and cross-share expertise within the data analytics space.
Among the themes covered were –
A. Leadership, Strategy and Organization: Realise the Value
B. Master Data Management: Curate Your Most Critical Data Assets
C. Analytics: Reshape The Entire Organization
D. Governance: Maximise Leverage and Control Chaos
E. Architecture and Technology: Modernise the Foundation
Read more about the Gartner Data and Analytics Conference 2017 here.
A main topic was how to build and execute effective, holistic data and analytics strategies within organizations. As such, Nugit found it fitting to talk about how to do this with the foundation of any business – its people. We asked the floor “Fact or Fiction: Anyone can be an Analyst.” But before we get to the conclusion of that discussion, here are 3 important questions that we feel any organization needs to ask itself:
FACT OR FICTION NO.1
Analyst: “50 – 80% of my time is spent data wrangling so I don’t have time to tell great stories.”
FACT: While this statement is a fact, it doesn’t have to be. Back in the day, data analysts and scientists were superstars. They were the cool kids who could do things that others couldn’t, and in some organizations, they still are. Where once data was an invisible trend that was built upon, protected and siloed, the future is all about empowerment.
The first stage was with dashboards – these tools were meant to help make sense of data, provide invaluable insights and most of all, assist in making people’s lives all-round easier with Business Intelligence. But the dashboard promise didn’t actualise, and data reporting still required a lot of work. As the velocity of data kept increasing, spreadsheets and Excel reports kept crashing, analysts and marketers alike were struggling to keep up… Things need to be scalable.
FACT OR FICTION NO.2
“People like reading data on spreadsheets.”
FICTION: The fact remains that we’re all visual. The brain is hardwired to receive visual input. We take mere seconds to attach meaning to an image, as opposed to reading rows and rows of statistics. Beyond that, there’s also the concern of accuracy and clarity.
As stated earlier, data wrangling takes up too much time. Diminishing effort at each step means there’s not much left in the actual delivery, i.e. no time left for “cool” stuff like visualizations. Traditionally, the best analyst in your company could do this, but unfortunately, in a typical company, the quality of Business Stories quickly degrades as you move to the typical report. It hasn’t been scalable and it’s not consistent. With the velocity of data flowing through a company ever increasing – consistency and scalability are even more important, yet the solution remains very elusive for them.
FACT OR FICTION NO.3
“You need to know how to write scripts and macros to be an analyst.”
FICTION: Where once it used to be all about technical skills and who was “smartest”, thanks to the internet, it’s now about who is best at Googling. This paradox exists in Data as well. It’s now no longer about the person who can write the best script, (technology handles this, or will soon), but it’s about the person who knows the best questions to ask of the data, how to interpret it and then tell the best stories. Intelligence has changed, and you now need creative people to help you with analytics; storytellers who can translate your data into narratives and ask really good questions of the data. These people CAN be analysts, and will probably be better at it than traditional analysts. And hiring them is what smart companies are doing.
So are your new hires bringing the right skillsets to the table?
Related post: Dashboard Dinosaurs versus Next Gen Analysis
In the future, there will be automated pipelines, with beautiful data visualizations that allow self-service, on-demand analytics, across multiple channels. Natural language insights will highlight important trends and tell stories – it will be beyond just a bunch of charts with numbers requiring hours to pore over. The best part? It’s going to be really easy to use and understand. This is good news because there are not enough analysts. You need the technology in order to help scale the workforce. The reality is that data shows no signs of slowing down, and is being used differently by different departments. It’s everywhere but fragmented, without a good interface or single source of truth.
In short, the answer is yes, with the right tools anyone can now be an analyst, and several smart organizations are making this shift by empowering their people and making their data accessible. The real question is if you’re a driver of the change or an obstacle.