Big Data Needs Big Data Scientists
Anders Liu-Lindberg
Leading advisor to senior Finance and FP&A leaders on creating impact through business partnering | Interim | VP Finance | Business Finance
If you really want to extract value out of big data you need to invest in doing so. Like with anything else you want to become good at it can’t be something you do when everything else is done and you have some time to spare. As part of my series “The CFOs Roadmap To Transforming Finance”, we’re now looking into what it takes to become a winner in the game of Big Data.
The CAO and the Analytics Analysts
Almost two years ago I reflected on how the development in Big Data affects the Finance Function in “The CAO and The Analytics Analyst”. The first question a finance professional should ask is should analytics and Big Data be a part of the finance function, a part of the business or a separate function altogether? From the past discussion, it seems that there’s no room for adding another CXO to the executive suite as it will require significant funding. Also, it has to be clear that there’s one set of numbers in a company and while you can discuss who should own them it shouldn’t be spread out on business functions, an analytics function, and Finance. I’ve previously argued in “How Finance Can Become An Analytics Powerhouse” that the numbers and the analytics function should be owned by Finance. Finance, of course, needs to serve its (internal) customers and deliver the necessary insights for the business to add value. An enabler of that is embedding finance staff into the business functions and letting them specialize in Sales, Operations, Marketing etc. Only when specialized will they understand the business well enough to challenge line managers and deliver value-adding insights. That leads to the next question. Can you be a business expert AND an analytics expert at the same time?
Terabytes, algorithms and a whole lot of numbers
At first glance, I’d argue a clear no. The simple reason for that is that just like the finance people embedded in the business functions need to specialize in their specific function the so-called data scientists need to do exactly the same. They need to continuously hone their skills within data extraction, data analysis and data synthesis coming up with answers to complex business issues. Then you say how can they do that if they’re not supposed to spend time on understanding the business? Clearly, there need to be meetings taking place between line managers and data scientists for requirements to be agreed upon but more likely than not translators will be needed (to be discussed next week). Essentially data is all the same and the task for the data scientist is to find patterns in the data. This requires sifting through terabytes and more terabytes of data using sophisticated algorithms and generally just analyzing a whole lot of numbers or words. This is no easy task indeed and calls for a specialist. What it then means and how it can be applied in a business sense (s)he will leave the business and the finance people embedded in the business to figure out.
It’s time to ditch the simplified view
Now that you’re about to invest heavily in Big Data and Big Data Scientists it’s naturally also time to clearly define what exactly is meant with Big Data. I’m no expert so I can’t do it for you but can only try to point you in the right direction. As highlighted in this paper there’s a significant divergence as to what Big Data means and I think we can all agree on that if you’re getting involved with something you don’t really understand the risk of you failing is a lot higher. So while just creating an Advanced Analytics or Big Data team might sound appealing you need to have a strategy for this area. One of the main points will be to simply agree on what Big Data means to you and then the next step is how can you extract value from it. Not until you’ve got the strategy laid down should you start to invest and indeed you need to invest as simply thinking you can convert some of your finance or IT people into Big Data Scientists means you still haven’t understood what Big Data is.
What’s your strategy for Big Data? Have you hired a lot of Analytics Analysts and really smart people with Ph.D.’s in Mathematics or Statistics? Perhaps you even have a success story to share? I would love to hear it! At Maersk Line, we’ve already done quite some work on this and certainly also seen good value from it but it’s only just begun and it’s exciting to see what the future holds. As always let me know what you think by liking, commenting and sharing so we can get the discussion going.
For previous posts in the series please see below:
The CFOs Roadmap To Transforming Finance
How To Fix Your Basic Finance Function
Finance Systems For The 21st Century
I also encourage you to take a tour of my old posts on finance transformation and not least “Introducing The Finance Transformation Nine Box” which is really that starting point for the transformation. Last but not least, you should join my Finance Business Partner Forum where we will continue to discuss this topic.
The Skills Of A Finance Business Partner
What Finance Business Partnering Really Is
You’re A Finance Business Partner, Now What?
Case Study: Becoming A Finance Business Partner
Why We Need Business Partnering Transformation
How To Define Finance Business Partnering 2.0?
Don't Explain Yesterday. Predict Tomorrow!
Now You Wish You Were Beyond Your Budget
5 Ways For Finance To Seize The Day In 2016
There Is A New Kind Of CFO Needed In Town
Finance Transformation Should Be All About... People
Why We Need Business Partnering Transformation
How Finance Can Help When Business Is Bad
Why Accountants Are An Endangered Species
How Finance Can Become An Analytical Powerhouse
How To Speak Finance In A Non-Finance World?
Anders Liu-Lindberg is the Senior Finance Business Partner for Maersk Line North Europe and is working with the transformation of Finance and business on a daily basis. Anders has participated in several transformation processes amongst others helping Maersk Drilling to go Beyond Budgeting and transformed a finance team from Bean-counters to Business Partners. He would love the chance to collaborate with you on your own transformation processes to help you stay out of disruption. If you are looking for more advice on how to get the most of LinkedIn Anders also has a few tips to share as well as if you want help in your job search. Don’t be shy! Let’s get in touch and start helping each other.
Multilingual Leadership Coach / Unlocking leaders’ freedom to focus on high-impact goals by empowering their teams / Executive Coach / Business Coach
6 年It seems to me that what we generally call Big Data involves different solutions such as data mining, data analysis, machine learning, AI... The first challenge I see as a finance person is understanding all these concepts and see how they can apply to the specifics of our company. As business partner we need to create specific user cases that will allow the rest of the management to understand the potentials gains we could achieve. Only then can we have an overall vision encompassing every department and defining the priorities and roll out plan that a high specialized team will deliver. As finance teams are already responsibles for analysis, reporting and systems it seems a natural place to create data science teams.
.
8 年Big Data scientists are more useful to the Big Data Tools developers. Big Data scientists can embed complex math algorithms in software to be used by end users. Few big companies that are employing Big Data scientists is because needed tools are not available.