Earnings per share (EPS) is a key indicator of a shares value.

It is a simple calculation: Total earnings divided by the number of shares issued.

As a general rule, increases in earnings per share reflect a growth in earnings and are an indicator of a fundamentally sound business. Companies that have consistent growth in their EPS typically are rewarded by increases in their share price.

Yet, EPS does not always show meaningful increase in revenue.

An example of financial engineering is the manipulation of EPS to show growth when earnings are static or declining. [Tweet This]

A recent example has been IBM’s strategy of share buybacks.

Over the last ten years or so IBM has focused on reducing the number of shares in play rather than on increasing earnings at required rates.

This meant that EPS was showing consistent, strong growth that were not necessarily indicative of the underlying growth in revenue of the business. This is the principle reason that the recent (Q3 2014) financial miss has been slated by many analysts.

Analysts are questioning IBM’s strategy which has been to inflate earnings per share by reducing the number of shares available to the market. Many analysts argue that this cash would have been better spent on investments for growth — such as R&D. They argue that share buy backs – while having a role to play in increasing investor value – are not a reflection of the company’s ability to grow earnings.

A key challenge for decision makers is to understand the fundamentals of a report.

3 businesses may meet EPS growth targets of 15% per annum.

Business 1 did this be increasing earnings through increased sales of core products – an indication that the company is on a sound track.

Business 2 may also show increased earnings – but in this case they made the decision to close down a key production facility and sell the assets. This exceptional earning helps them to meet EPS targets, but at the expense of next year’s profits as they have now lost the ability to meet projected demand,

Business 3 may have inflated up EPS growth through share buy backs. This approach can deliver fantastic value to share holders – particularly if shares are undervalued. Yet it is not a substitute for genuine growth and cannot be sustained indefinitely

We have the same formula for assessing the health of each business – yet we have three very different contexts. [Tweet this]

Data governance creates context.

Without context our results are open to interpretation.

EPS is just one example of a key metric that can be interpreted in different ways.

Different business units, or managers, may apply their own interpretations to various metrics – budgets, expenses, growth, profit, head count, and many more – resulted in confusing and conflicting results.

Or they may source their data from different systems – creating different numbers.

Results that seem fine when viewed at department level may create significant confusion when aggregated and rolled up to an enterprise view.

The result?

Executives (or shareholders) cannot trust the data and the BI or EDW project becomes yet another expensive failure by IT

The solution?

Context must be provided for each report, and each calculation, to ensure that we understand how a result was derived

How did we calculate EPS?

Did we include exceptional earnings?

What was the impact of share buybacks?

Where did we source the data?

What was the quality of the underlying data?

Which period did we measure?

Can we map results from one system to results from another?

Are key metrics consistent across systems, geographies or business units?

These are data governance questions that are key to supporting the data driven business.

Context is the difference between trusted data and failed BI [Tweet this]

Context allows decision makers to perform their own due diligence and ensures that we are making informed decisions.

Context may be captured in the form of a business data glossary, as business data lineage, and as linked between business definitions and technical metadata.

Do you have context for your data?

This post does not constitute financial advice. Before you consider buying, or selling, anything please do your own due diligence.