Have you been dead by analysis?
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Have you been dead by analysis?

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How Data & Analytics created value at Uber

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Death by analysis - sounds dramatic, doesn't it? Well, it's not *quite* a matter of mortal threat, but it is something that most Finance and Data & Analytics professionals will have had the misfortune of experiencing.

It's not going to analyze itself

Here is the standard workflow for many (I hesitate to say "most") finance professionals dipping their toe into the analysis.

First, they take a look at their enterprise resource planning (ERP) platform (or platforms) and identify information that might be relevant to the question or task at hand. That data gets extracted in whatever format is available, and then imported to Excel where a pivot table is produced.

Then, the finance professional starts looking for...what, exactly? Trends, patterns, and occurrences that look like they might be statistically notable. All too often this work is essentially unstructured. The professionals in question don't really know what it is that they're hoping to see, let alone what they might do with the information they glean. It's not just like looking for a needle in a haystack - it's like looking for a needle in a haystack without ever having seen a needle before.

If you die in analysis, do you die in real life?

This Sisyphean way of working might be referred to as "death by analysis". I think it's one of the primary reasons for the stress and burnout we see in so many Finance Functions. It's putting the brakes on innovation - and, crucially, it's preventing us from creating value through insight.

So here's a better way of working.

First, begin with a clear objective. What's the problem that you are trying to solve, or the question you are trying to answer? What's the process you are attempting to streamline, or the strategic issue you are trying to navigate?

The only way to answer this crucial first question is by consulting with other stakeholders across the business. The modern Finance Function is cross-functional and based on inter-disciplinary cooperation. This means getting your hands dirty across the business, understanding what it is that other parts of the organization need, and how you can support them.

Having identified and understood the challenge, sketch out the form that a valuable insight might take. Then, using the information and expertise you've gathered from across the organization, it's time to form a hypothesis. What do you think is happening? What do you think might present itself if the relevant data were explored? How do you think the business problem can be best solved?

Hypothesis, analysis, insight

Next, analyze the data to test your hypothesis. This is where your Data & Analytics skills come in - or, crucially, where you might seek support from other teams or individuals with the relevant skills. As the Finance Function matures and changes, the overlap with D&A is growing. While these are two distinct skill sets, the intersection between the two is where we're going to solve the problems of today and tomorrow.

Once you've tested your hypothesis, it's time to present the insight you've generated. The manner of that presentation is crucial if you want to create better outcomes - and that will be the topic of the next article in this series.

Being more mindful and purposeful about the way you analyze and interpret data is the number one thing you can do for your career right now. It's the key to generating insight - and that is the way we unlock the value of the Finance Function. Get started today, and make sure you subscribe to receive the next articles in this series.

This was the fifth article in my latest series about the "Data to impact journey" You can read previous article(s) in the series below.

From data to impact - the Holy Grail of Finance

The power of harnessing data for Finance

What cleaners and finance professionals have in common

The limits of data visualization for the Finance Function

While you await future articles why not read my previous series on Data & Analytics below?

Finance and Data & Analytics - better together

Does your company need a Data & Analytics team?

Can a finance professional "do" Data & Analytics?

Why Data & Analytics always wins

The case for Finance "owning" Data & Analytics

Why Data & Analytics struggle with the "last mile" of impact

Let's end the war between Finance and Data & Analytics

How to create value with Data & Analytics

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You're The User Of AI. Yes You, So Take Charge!

Blip. Blop. Accounting Robot. Are You Ready?

Are You Ready For Robotics Process Automation?

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Anders Liu-Lindberg is the co-founder and a partner at the Business Partnering Institute and the owner of the largest group dedicated to Finance Business Partnering on LinkedIn with more than 10,000 members. I have ten years of experience as a business partner at the global transport and logistics company Maersk. I am the co-author of the book “Create Value as a Finance Business Partner” and a long-time Finance Blogger on LinkedIn with 115,000+ followers and 200,000+ subscribers to my blog. I am also an advisory board member at Born Capital where I help identify and grow the next big thing in #CFOTech. Finally, I'm a member of the board of directors at PACE - Profitability Analytics Center of Excellence where I support the development of new analytics frameworks that can improve profitability in companies around the world.

Bahman Mohajerin

Senior Manager at Bayat Rayan

2y

A clever title: analysis paralysis. It tells all.

Ryan Donaghy

Advance Your Finance/Data Career 📊 with English Communication Skills 📈 | Specialist English Communication Skills Coach

2y

It is very easy to reach a "needle in the haystack" point with analysis. This is why your "hypothesis, analysis, insight" approach is often more effective, Anders. When we have a specific pattern or relationship that we're looking for, most of the data becomes immediately irrelevant, which means it's more like "finding a needle in a box of cornflakes" — much more manageable!

Christian Frantz Hansen

Finance Management Consulting | CFO Services | Finance Business Partnering | Interim Finance Support | FP&A | Finance Learning & Development

2y

When trying to come up with relevant insights, there are two approaches: 1. Start with the data (bottom-up) This is where you explore data in the hope of finding something relevant or interesting. This approach comes at a significant risk of ending up in analysis paralysis. 2. Start with the audience (top-down) This is where you identify the challenges of your stakeholders first, and then use analysis to come up with relevant recommendations. This approach is less like to lead to analysis paralysis, since you have a clear problem to solve. In my opinion, some finance professionals spend too much time on approach 1 and too little time on approach 2. 😊

Neema Gray

B2B Pricing & Product Specialist | Unlocking Growth & Margin Improvement Opportunities for Manufacturers & Distributors | Double-Digit Growth | Value Creation | Monetisation | Product Innovation | Business Transformation

2y

This is so true Anders Liu-Lindberg.

Johann ROBETTE

Beyond grand theory, I help companies ensure their Supply Chain actually drives value! 🎯💰

2y

Love this... "It's not just like looking for a needle in a haystack - it's like looking for a needle in a haystack without ever having seen a needle before." 👍👍

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