Big Data: The All-Important 90/10 Rule
Bernard Marr
?? Internationally Best-selling #Author?? #KeynoteSpeaker?? #Futurist?? #Business, #Tech & #Strategy Advisor
In this post I outline my 90/10 rule for big data initiatives in businesses. The post was first published in my column for Data Science Central.
The phenomenon of Big Data is giving us ever-growing volume and variety of data we which we can now store and analyze. Any regular reader of my posts knows that I personally prefer to focus on Smart Data, rather than Big Data - because the term places too much importance on the size of the data. The real potential for revolutionary change comes from the ability to manipulate, analyze and interpret new data types in ever-more sophisticated ways.
The SMART Data Framework
I’ve written previously about my SMART Data framework which outlines a step-by-step approach to delivering data-driven insights and improved business performance.
1. Start with strategy: Formulate a plan – based on the needs of your business
2. Measure metrics and data: Collect and store the information you need
3. Apply analytics: Interrogate the data for insights and build models to test theories
4. Report results: Present the findings of your analysis in a way that the people who will put them into effect will understand
5. Transform your business: Understand your customers better, optimize business processes, improve staff wellbeing or increase revenues and profits.
My work involves helping businesses use data to drive business value. Because of this I get to see a lot of half-finished data projects, mothballed when it was decided that external help was needed.
The biggest mistake by far is putting insufficient thought – or neglecting to put any thought – into a structured strategic approach to big data projects. Instead of starting with strategy, too many companies start with the data. They start frantically measuring and recording everything they can in the belief that big data is all about size. Then they get lost in the colossal mishmash of everything they’ve collected, with little idea of how to go about mining the all-important insights.
This is why I have come up with the 90/10 rule – When working with data, 90% of your time should be spent on a structured strategic approach, while 10% of your time should be spent “exploring” the data.
The 90/10 Rule
The 90% structured time should be used putting the steps outlined in the SMART Data framework into operation. Making a logical progression through an ordered set of steps with a defined beginning (a problem you need to solve), middle (a process) and an ending (answers or results).
This is after all why we call it Data Science. Business data projects are very much like scientific experiments, where we run simulations testing the validity of theories and hypothesis, to produce quantifiable results.
The other 10% of your time can be spent freely playing with your data – mining for patterns and insights which, while they may be valuable in other ways, are not an integral part of your SMART Data strategy.
Yes, you can be really lucky and your data exploration can deliver valuable insights – and who knows what you might find, or what inspiration may come to you? But it should always play second-fiddle to following the structure of your data project in a methodical and comprehensive way.
Always start with strategy
I think this is a very important point to make, because it’s something I often see companies get the wrong way round. Too often, the data is taken as the starting point, rather than the strategy.
Businesses that do this run the very real risk of becoming “data rich and insight poor”. They are in danger of missing out on the hugely exciting benefits that a properly implemented and structured data-driven initiative can bring.
Working in a structured way means “Starting with strategy”, which means identifying a clear business need and what data you will need to solve it. Businesses that do this, and follow it through in a methodical way will win the race to unearth the most valuable and game-changing insights.
I am always keen to hear your views on the topic and invite you to comment with any thoughts you might have.
Here at LinkedIn and at Forbes I regularly write about management, technology and the mega-trend that is Big Data. If you would like to read my regular posts then please click 'Follow' and feel free to also connect via Twitter, Facebook and The Advanced Performance Institute.
Here are some other posts from my Data Science Central column:
- What is Big Data (Infographic)
- Is Microsoft Putting Big Data At The Heart Of Their Business?
- The 5 Vs of Big Data (Infographic)
- 4 Ways Big Data Is Transforming Healthcare
- How Big Data and the Internet of Things Create Smart Cities
About : Bernard Marr is a globally recognized expert in big data, analytics and enterprise performance. He helps companies improve decision-making and performance using data. His new book is Big Data: Using Smart Big Data, Analytics and Metrics To Make Better Decisions and Improve Performance'.
Photo: Shutterstock.com
Design Specialist at AT&T RETIRED
9 年Data rich and insight poor...good post!
Retiree at County of Orange, CA
9 年Years ago I took a computer course. The simple framework was 1) Input, 2) Throughput, 3) Output, 4) Impact. Seems like "Impact" is similar to your "90% Strategy."
Customer Business Outcomes Leader at Microsoft. Digital Transformation: Practical, Prescriptive & Purposeful.
9 年Why is big data analytics any different from any other data analytics? I am sure, the same 90/10; 80/20 SMART approach would have been taken by those who succeeded in delivering actionable insights. None of the data is churned manually, so whether it is 100GB or 10TB.....it is the velocity at which data is hitting you is what makes things complex. The ability to react to this velocity and find the small data in that big data is what determines the level of action.
Senior Solutions Architect at InnoVent Rental & Asset Management Solutions
9 年This how you take a concept from 1981, bind it with modern buzzwords and the resulting spin is best selling. It's basic system architecture and database design concepts. Nothing new really, although a re-iteration of known topics.
Market Research Analyst | SME Consultant | Economist
9 年We've all experienced it. Marr hits the nail-on-the-head with- -"...frantically measuring and recording everything they can..." Ultimately getting lost in the data maze and still trying to figure out why we don't have a clear answer or direction.