top of page

UNCOVERING

SURPRISING

INFORMATION

IN FINANCIAL

STATEMENTS

A primer on Operating Model design and value driver analysis.

In this article, we will discuss the how an operating model for your enterprise can be developed using sensitivity analysis. The tools we will discuss will help you better understand the performance of a company and prioritize action plans to increase shareholder value. I will specifically discuss the use of sensitivity analysis and "what-if" scenarios to uncover information that may startle even the most experienced financial analyst. If you read the article completely you will have an opportunity to download a free financial statement analysis tool!

 

In the last 20 years I have worked for, and provided advice to, C-level leadership at major enterprises. First in the corporate strategy function for GE/NBCU, later as a junior executive for Ernst & Young's advisory practice and a partner with IBM's Global Services consulting. As you engage across companies and industries a pattern of common issues and solutions arises.

 

Most companies look to make a strategic change in their operating model in one of the following circumstances:

  • Merger integration or divestiture

  • Organizational restructuring

  • Regulatory changes

  • Pressures or changing industry dynamics

  • The emergence of a new competitor

  • Availability of new technologies (cognitive, social/mobile, cloud)

  • To increase service operations effectiveness

Following Amazon's announcement of the acquisition of Whole Foods brand, Kroger, Supervalu, Costco and Sprout's farmers stocks all tumbled.  Amazon's acquisition shook the very foundation of the grocery business and while Amazon went on immediately slashing Whole Food prices, Kroger swiftly announced it was considering to divest of its convenience stores as a protective measure.

The grocery industry is ripe for a change and Amazon is undoubtedly going to make this a massive one: transforming delivery and fulfillment, vertical integration and sophisticated leverage of its digital assets with this new brick & mortar presnce.

So if you were the CEO of Kroger how would you go about examining your Operating Model?

Each strategy advisory approaches this differently: McKinsey focuses on governance, performance, leadership and change management without a formal operating model design. BCG has their "operating for value framework" to help understand how processes create value and Booz Allen's focus on "Organizations, People and Performance" focuses on decision making as a driver of performance (Bain does this as well). Accenture focuses on supply chain strategy & logistics as key drivers of operating model efficiency and EY has their "value driver framework".

There is a analytical way to develop a "future state" for transformation which allows you to model the outcome using  "what-if" scenario analysis.

It's all about the levers

As the senior leader of your enterprise you have a (virtual) panel of levers which you can pull the wrong combination can lead to productivity loss, employee morale issues or financial distress. The right combination can overcome external pressures and drive growth.

 

How do you know which "levers" to pull?

In order to map out the dependencies and impact that these "drivers" have on your company's performance we need a metrics framework.  There are many ways to skin the cat so I will share with you a few ways this is done.

First let's map out the dominant corporate financial drivers as a generic model. I refer to this as the right side analysis (to the right of the main "Company Performance" box.

Right side analysis: Financial drivers

These financial metrics are important because they answer the question where will the value be created? Of course this value model tree may look a bit different depending on your industry. For instance, an insurance carrier such as MetLife may break apart revenue growth to Premium-based revenue growth vs. Non-Premium revenue growth (such as institutional investments, "float" revenue, bonds, and fees).

Let's start by adding more details to the right side analysis. Later on we will align strategic imperatives to this model in what I call the "left side" analysis.

 

Here's an example of operational drivers for a media company looking to increase its revenue from digital operations:

In this diagram we are focusing on revenue growth and costs, so capital utilization is grayed out because it is not the focus of our attention for now

Right side analysis: Financial & operational drivers

The green boxes are the operational drivers which affect the financial levers. For instance if this media company can improve its ability to sell ads across mobile, social and web then advertisers will likely spend more with them, thus driving Revenue Growth. Similarly they can throttle pricing based on customer segementation and offer deeper discounts not only based on budget but campaign profitability (some ad campaigns are more costly to execute than others)

Ok. Let's take this one step further and introduce operational levers by which we can improve performance of the operational drivers:

Right side analysis: The addition of lever measurements

The operational levers answer the question What are the quantifiable ways to improve the performance of operational drivers?

The last step is to define the actual metrics, known as Key Performance Indicators (KPIs). This is the data you need to collect and report on. KPIs can include Day Sales Outstanding (DSO), Cost of Goods Sold (COGS) or in the case of this media company - the amount of time sellers spend conducting selling activities (vs. admin overhead filling out CRM forms, for instance).  We now scale back the model to depict the financial drivers and KPIs (white boxes):

Right side analysis: KPI metrics

Each KPI (white box) is derived from an operational driver from prior charts. There are several takeaways from this representation you should note:

  1. Every KPI ultimately rolls up to a major financial driver category. As such this implies inter-dependency between the drivers: change one and you affect the total outcome of the entire financial driver combination.

  2. It is possible to create opposing impacts with no net effect: One KPI can positively affect revenue while being negated by another.

  3. No single business function "owns" the outcomes: the entire business and all key stakeholders much collaborate to produce a desired impact on financial performance

Left Side

Strategy Alignment

As you look at the KPIs you start to posit new corporate initiatives. It is helpful to list out those initiatives (and ones that are underway) on the left side of the model.

 

This is what I call the "left side analysis": we remove the "company financial performance" and match the initiatives with the first level financial drivers they are designed to impact:

Right Side

There are many ways this can be developed further, far beyond the scope of this article. Be it fair to say that this entire effort is where strategy experts earn their keep: facilitating development sessions with key leaders and stakeholders, vetting with subject matter experts in the organization and testing out theories with real-world customers (internal or external). Let's stop here and review our work so far.

 

We have seen a methodology used to represent company imperatives, align them to financial drivers, explain how those drivers can be explained by operational drivers and come up with the metrics (KPIs) used to measure the performance of operational metrics.

 

Now we move on to the meat of our topic: sensitivity analysis.

What If? Sensitivity Analysis

In the course of my career I have come across many variants of this analysis:

  • Power of 1 (developed by the founder of Finnlistics, a highly recommended tool for this type of analysis),

  • What-If /goal seek scenario modeling, built into Excel

  • Sensitivity analysis and value driver analysis.

 

The approach is simple: if we are creating a new operating model for our company (using the mapping you read about earlier) - we will have many metrics (KPIs) which we can target to improve. 

  • What is the co-dependency between the KPIs?

  • Which ones will have the greatest impact at the lowest effort/cost?

This can be done from a bottoms-up approach and a top down.

In bottoms-up - you build a large excel spreadsheet with all the KPI relationships baked into the formulas

In a top-down approach you simulate a "1 point" change in a financial metrics and model the impact on the overall company performance.  This is the approach we will discuss today, and is the way that the folks at Finlistics developed their tool.

bottom of page