FP&A: Innovations in Financial Analytics to Support Organic Growth and Business Strategies

THE RESOURCE FOR CORPORATE FINANCE, ACCOUNTING & TREASURY PROFESSIONALS

James MyersDirector, FP&A Strategy Consulting

FP&A: Innovations in Financial Analytics to Support Organic Growth and Business Strategies

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Learning Objectives

After participating in this event you will be able to:

Discover how to apply the Lean Analytics Cycle (Metrics > Hypothesis > Experiment > Act) to your business

Learn the difference between vanity and actionable metrics

Practical examples of how actionable metrics can be used to drive change in an enterprise

THE RESOURCE FOR CORPORATE FINANCE, ACCOUNTING & TREASURY PROFESSIONALS

James MyersDirector, FP&A Strategy Consulting

FP&A: Innovations in Financial Analytics to Support Organic Growth and Business Strategies


What does the future hold?

What will happen next time you look for a traditional job

http://m.entrepreneur.com/article/228176#!



What does the future hold?


What will happen next time you look for a traditional job



Case Study: How Google Overhauled its Finance Department By Andrew Deichler 2013-09-16

http://www.afponline.org/mbr/reg/res/reg_news/Case_Study__How_Google_Overhauled_its_Finance_Department.html

In late 2008-early 2009, Google decided to expand finance. But instead of hiring a lot of additional finance practitioners, the company instead hired engineers and business intelligence professionals.

Google then stopped hiring in finance altogether later in 2009 and determined that any incremental growth would be on an emergency basis. Thomas explained that Google CFO Patrick Pichette adheres to the Six Sigma methodology. "He said, 'You need constant improvement. As time goes on, you should be getting better and better at what you do. And if this is working out where we're hiring all of these BI and technical people, you should be able to keep up with your workload,'" Thomas explained.

Over time, Google reduced its finance workforce yet still maintained its productivity. But how did it do so? "We did three things," said Thomas. "We eliminated, automated and simplified."

http://www.afponline.org/mbr/reg/res/reg_news/Case_Study__How_Google_Overhauled_its_Finance_Department.html


Building Blocks of FP&A

Historic Reporting- Maintain control and

integrity of information - Traditional analytics- Financial reporting

Historic Reporting- Maintain control and

integrity of information - Traditional analytics- Financial reporting

Future predictability- Revenue planning- Budgeting- Managing financial risk

Future predictability- Revenue planning- Budgeting- Managing financial risk

Strategic Alignment- Lean analytics- Sales process development- Business model & strategy

deployment and optimization

Strategic Alignment- Lean analytics- Sales process development- Business model & strategy

deployment and optimization


Why do I think we are all in the right place

Technology companies are leading the charge of hiring CFOs with deep experience in data analytics and an aptitude for driving the sales process. (CFO.com)

(New Tech CFO’s) spend less than half of their time on traditional finance functions like reporting, treasury, tax and investor relations. Instead, they engage in minutely detailed data analysis, drive the sales process and act as lead executors of the company’s business model and overall strategic direction

“…‘new breed’ of CFO, the analytical piece is a big differentiator…” says Hightail’s Sizer, 47 “Folks like me are in high demand today to solve a data problem.” That is, most companies, but especially online technology companies, have massive amounts of data and must figure out how to use it to drive business performance improvements

“It depends on the company’s size, but the most successful CFOs I know have no inhibitions against rolling up their sleeves,” says 40-year-old Sloat (Zuora).

http://ww2.cfo.com/leadership/2013/07/a-new-breed-of-cfo/

http://ww2.cfo.com/leadership/2013/07/a-new-breed-of-cfo/


What we are seeing in the market place

Business Intelligence

Big Data

Big Incite

Business Strategy Sales

FP&A Professionals


My Vision

In the future, corporations of all sizes will become more dependent on their FP&A teams for direction.

Both in short term tactical business decisions to long term strategic initiatives, analytics will play a greater role offering support during uncertain times.


Part 2: Theory


Definitions

Innovations in Financial Analytics to Support Organic Growth and Business Strategies

• Business strategy: what to provide, to whom, on what competitive basis

• Organic growth: R&D funding, geographic expansion, product and service expansion

“A startup is a human institution designed to deliver a new product or service under conditions of extreme uncertainty” Eric Ries


Toughest executive team decisions

Source: Deloitte CFO Signals, Q3 2012

60% of CFO’s cite difficulties related to business strategy another 60% cite struggles with organic growth decisions


How can FP&A help to grow business organically

Lean StartupSpending the least amount of resource (time and money) to discover a sustainable business model, for businesses that operate in high uncertainty

Lean analytics: the tools that measure how sustainable a business is.

A business can be sustainable in 1 of 3 ways:1. Sticky - people keep coming back2. Viral - word of Mouth3. Paid – Advertising/Sales teams

Techniques to make smarter business decisions, with reduced resources (time and money) during times of high uncertainty


Myths about Lean Startup

Myth: Lean Startup = Cheap/Low quality:• It’s not about cost, it is about speed. Using these principles

companies waste less money, because they use a disciplined approach to testing new products and ideas

Myth: Lean Startup = Startup:• The Lean Startup methodology applies to all companies that face

uncertainty about what customers will want and include both large and small companies

Myth: Lean Startup = Agile:• Agile is a software development methodology using iterations. The

Lean Startup is a management methodology focused on building a sustainable business

Myth: Lean Startup replaces vision:• The Lean Startup methodology doesn’t replace vision but offers a

range of tools to help realize the vision


Vanity metrics - measurements that give “the rosiest picture possible” but do not accurately reflect the key drivers of a business. Numbers or stats that look good on paper, but don’t really mean anything important.

Actionable metrics – A metric that can lead to informed business decisions and subsequent action.

So what is a Vanity Metric and what are the alternatives

Wikipedia


Melting Ice Cube thought experiment

The Black Swan – Nassim Nicholas Taleb


Part 3: Examples


Introducing the lean analytics cycle

Four-step process: 1. Figure out what you want to improve2. Create an experiment3. Run the experiment4. Measure the results and decide what to do

Hypothesis

Metrics

Experiment

Act


Step 1: Figure out what to improve

1. Identify an area of your business that you would like to improve, e.g. Increase sales in retail; Increase in ASP for mobile sales. (if there are many, the best is to stack rank the list and start at the top)

2. Write down the assumptions you are currently making regarding this area of business and list them in order of importance.

Hypothesis

Metrics

Experiment

Act


Example 1 – Accessory Shop mobile App

Areas I would like to improve:1. Increase the ASP per session back to the $0.7 2. Increase the number of sessions

Hypothesis: Building awareness of other products will increase the ASP per session

Assumptions I’m making (listed in order of importance):3. Users don’t realize that they can select other products4. Users can’t navigate back to the selection page to select a

new product easily5. Users want to buy accessories for devices other than their

own phone (proven)

Step 1: Figure out what to improve - ExamplesHypothe

sis

Metrics

Experiment

Act


Step 2: Create the experimentHypothe

sis

Metrics

Experiment

Act

1. Decide on the target audience:Who are the target audience? Think of analytics in terms of people and actions, what do we want them to do? Be specific about what group of people we are going to address, sometimes it’s easier to focus on a smaller group than a larger one.

2. Decide on the experiment:What action do you want them to take? How many are doing it today and will the experiment have an impact and create change. How well are you motivating them to change

3. Decide on how you will measure it (metrics and time frame)How are we going to measure the change from before the experiment to after? Remember we want specific actionable metrics

4. Decide on resultSetup your upper and lower limits:• below lower = Fail; above upper = Pass, in between =

more testing


Step 2: Create the experiment - ExamplesHypothe

sis

Metrics

Experiment

Act

Assumptions to be tested: Users don’t realize that they can select other products

1. Decide on the target audience:Target audience – high end mobile device users of the app as these are the most likely to also have another CE product e.g. Kindle, Xbox or iPad

2. Decide on the experiment:Turn off the automatic product selector, this will force the user to select their own product and in doing also see other available products

3. Decide on how you will measure it (metrics and time frame)Measure the number of times the user switches from one device to another device

4. Decide on the result (most important)Currently 4% switch devices from the original device, therefore <5% = fail and >15% = pass


Step 3. Create the experiment.Hypothe

sis

Metrics

Experiment

Act

1. Run the experiment• Many experiments can be run at the same time, but

ensure that there is no overlap which may cause interference– this could make it difficult to identify what has been causing the impact

• You may want to run different experiments on different cohorts (users with a similar characteristic) e.g. try one experiment with returning users and one with new users

2. Measure the results• Ensure that your measurements have all of the following

characteristics:• Accurate - be free from errors and omissions & a

complete set of data • Accessible - be easily understood and available

widely• Auditable - be able to go back to the source data to

prove that the report is telling the true story• Actionable - demonstrate a clear cause and effect

relationship so that you can take definitive action in response to it


Step 3. Create the experiment - ExamplesHypothe

sis

Metrics

Experiment

Act

1. Run the experiment• Experiment run for Wk. 39 for one week

2. Measure the results:

No. of users that switched phones

Wk 36 Wk 37 Wk 38 Wk 390%

1%

2%

3%

4%

5%

6%

4% 4%4%

6%

• Accurate – data checked for completeness and accuracy• Accessible – detail of data made available to the team• Auditable – backup data made available• Actionable – the change has a direct impact on the metric


Step 4. Measure and decide what to doHypothe

sis

Metrics

Experiment

Act

1. If the experiment was a success, celebrate a bit, then move to the next assumption/hypothesis or area of improvement

2. If the experiment failed spectacularly, we need to revisit our hypothesis and assumptions.

3. If the experiment moved the needle, but not enough to clear the goalposts, we should try another experiment.


Step 4. Measure and decide what to do - ExampleHypothe

sis

Metrics

Experiment

Act

Results: 6% of users moved to other products, therefore the experiment moved the needle, but didn’t succeed.

Hypothesis: Building awareness in the App of other products will increase the ASP per session

Assumptions1. Users can’t navigate back to the selection page to select a

new product easily 2. Users want to buy accessories for devices other than their

own phone (proven)3. Users don’t realize that they can select other products

(further testing)

Next experiment: Improve the navigation back to the product selection page.


Summary

• Lean Analytics: Metrics > Hypothesis > Experiment > Act is a cycle and the more cycles the more validated learning.

• The process is forward looking and therefore more scientific (as seen by the ice thought experiment)

• You must set an upper and lower limit – otherwise you will always succeed

• The process can be applied to any area of the business and has the most impact in areas of high uncertainty

• Lean Analytics does not replace strategy or processes, but it is one of many tools you should consider to help make better decisions faster


THANK YOU


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