Communications Consulting Worldwide
Frequently Asked Questions
Methodology and Intangibles
- What are you referring to when you talk about "intangibles"?
- What makes intangibles important now?
- How do intangibles affect a company's value/firm performance?
- Why do managers care?
- Isn't qualitative research the only real and reliable way to examine intangibles in corporations?
- How can intangibles be measured?
- How can intangibles me managed?
- How do you know if a component (Theme) measures what it is supposed to measure?
- Can you predict what affect a change on any one intangible would have on corporate performance?
- Can this analysis hold-up over time?
- Can you use this as a benchmark against competitors?
- How does this methodology compare with other valuation techniques?
Data and Process
- Overall, when you say you need data for the model, what type of data do you mean?
- What outcome measures/data do you want?
- What media measures do you want?
- What other measures/data can you include?
- What about competition?
- Do you want quarterly or monthly data for the analysis?
- How can you model with so few data points?
- How do multiple measures help?
- How do you estimate effects?
Methodology and Intangibles
What are you referring to when you talk about "intangibles"?
Intangibles refer to many different aspects of a business that are assets or creators or value but not included on a company's balance sheet. What they have in common is that they all drive economic performance, and they are all manageable yet often – until recently – unquantifiable. Intangibles include strategy and the ability to execute that strategy, specialized knowledge that a business brings to the table, R&D investments, communications, and brand management. Similarly, intangible assets include people, from human resources, to employee talent to management quality. And, also ideas, innovations, know-how, relationships, systems and work processes.
What makes intangibles important now?
Valuing assets in the industrial economy was vastly different than it is today. In an economy dominated by service businesses, it is logical that the bulk of the economic value being created would be of the sort not recognized in the previous century. Manufacturing inventory was quantifiable and the worth of a factory could be determined by assessing equipment value.
But today's economy – one based on benefits like knowledge, R&D, and innovation – requires an unprecedented challenge, valuing intangibles. We see that:
- Market to book ratios continue to increase
- The relationship between financial performance and stock price is decreasing
- Physical assets have become a liability
- Investment in brand development, training, and R&D now exceed total investments in tangible assets
- At least a third of a mature company's value is attributable to non-financial information
- There is increasing demand for global transparency
How do intangibles affect a company's value/firm performance?
Intangibles affect a company's value both directly and indirectly, meaning that they have influence on both the bottom line and tangible factors that affect a company's bottom line. For example, "customer relationships" is a category that encompasses brand management, customer service, and many other facets of a business's operation, all of them interrelated. And, some of the buzz-phrases of the past decade—customer intimacy, one-to-one marketing, the lifetime value of the customer—testify to the growing realization in the business world of its importance. Numerous studies have been done on companies linking their customer relations back to firm performance – and we can provide you with example case studies.
The bottom line is, improvement in key intangible drivers translates into increased market value. Our valuation methodology establishes the relationship between actual non-financial performance and value creation by identifying key performance measures that drive organization success and the intangible actions that drive them. In fact, intangibles, though not historically recognized as such, have always been drivers of corporate performance – and institutional investors who attribute a significant part of a company's market value to non-financial data, take intangibles into account in their analysis and earnings estimates.
Why do managers care?
In a volatile global economy, managers need a broad set of indicators critical to strategic decision-making. Management teams that rely wholly on reporting of their past and current financial performance are operating with incomplete and possibly inaccurate information about their enterprise. They are also missing a forward-looking view of the company and a significant opportunity to improve operating and capital market performance by examining data previously considered unquantifiable.
As market value to book value has steadily increased over the past 80 years (reflecting a shift from past to potential performance as the source of shareholder value), and US and European regulatory authorities have begun to address the imprecision in accounting for "goodwill," intangibles are now even more critical to explaining that gap. Investments in intangibles , which now exceed total investments in tangible assets, skew return on investment capital from historic norms. In fact, the percentage of a company's value that is unaccounted for by tangible assets has skyrocketed – anywhere from 50%to as much as 90% of its value.
Isn't qualitative research the only real and reliable way to examine intangibles in corporations?
No. While qualitative research can be rich in stories and information, qualitative data is not an end in itself. It cannot be measured, it cannot be linked empirically to bottom line performance and therefore, it does not, in and of itself, help executives and managers manage their business.
- First, one cannot be certain of drawing accurate conclusions from the stories; there will not be a representative set of data.
- Second, in corporations upper management will not find the stories contained in qualitative data to be sufficient proof to justify budget increases or the worth of a particular business unit's efforts.
- Finally, in order to manage something, it must be measured.
Qualitative research supports the understanding of intangibles, but it isn't an end in itself. It does not provide the measurement piece. There are two ways that we use qualitative research in understanding intangibles:
- One, to help understand an issue or issues and then to develop a closed-ended survey instrument to gather quantitative data to test empirically what trends we are finding in the qualitative research,
- Two, if quantitative data is scarce and a company wants to start from scratch in first collecting qualitative research and then developing a closed-ended survey instrument as above.
How can intangibles be measured?
Intangibles can be measured by creating a measurement model to approximate the value of individual intangible drivers. First, a company, business unit, industry or sector must be identified. Then, key intangible drivers for that unit need to be defined. Next, indicators need to be identified and constructed for each driver. Data from public and proprietary sources, including company and industry reports, expert ratings, government filings and special studies can be considered. Multiple measures for each driver from as many sources as possible, to reflect different aspects of the category, should be chosen to ensure a more comprehensive and reliable measure. Finally, using advanced statistical techniques, the ability of each value driver category to explain performance outcomes should be assessed, beyond what could be attributed by traditional accounting of assets and liabilities.
How can intangibles me managed?
Creating a measurement model of intangibles takes the fuzziness and subjectivity out of managing intangible drivers. It offers a yardstick by which to compute the impact of non-financial variables, based on widely acknowledged factors whose relative value has been rigorously tested and proven. Our methodology, for example, can be adapted to accurately reflect the changing sources of value and uses of knowledge as a dynamic metric. This type of measurement and modeling provides managers with a more complete view of the wealth creating potential of the companies, eliminating the partial and restricted view of a strictly financial perspective. It provides managers with an invaluable set of levers which can be adjusted to produce measurable improvements in organizational performance. The sort of metrics developed by this process can be institutionalized via management processes and/or software so that business unit or divisional goal setting, including compensation, can be measured and rewarded. This can be the ticket to a more efficient use of capital and resources.
How do you know if a component (Theme) measures what it is supposed to measure?
We use a multi-stage approach. First, we want to find multiple messages (or variables) to represent the theme (component). Usually three or four messages are adequate. This helps build up the Theme in terms of its definition and what it covers. We look for these messages in corporate supplied data, our own databases, and other publicly available data as necessary. Once we feel that we have found messages that adequately cover the themes we want to model, we then run several statistical tests – preliminary principal component analyses and factor analyses – to validate that the Themes explain what we intended them to empirically and that each Message is in the right place statistically. If it does not fit, then we can see statistically where else (i.e. in which Theme(s)) it would be a better fit, or that it does not fit into the model at all. Once these are done, we are ready to run a primary model.
Can you predict what affect a change on any one intangible would have on corporate performance?
Yes, with the modeling techniques we utilize, we can isolate the expected impact percentage (or effect) of a change in any one intangible driver on firm performance measures. This is exciting because it allows managers to know what changes to make in order to maximize the return on their investments.
Can this analysis hold-up over time?
Yes. A model that is created using robust indicators to define each intangible driver should hold up quite well over time and, in fact, be predictive of the effects of changes in drivers of firm performance across time.
Can you use this as a benchmark against competitors?
Absolutely. An excellent use of such modeling is as a benchmarking tool to compare one firm's overall value creation score with another, and also to compare driver against driver. This will tell a firm where to put emphasis in order to create a competitive advantage over competitors.
How does this methodology compare with other valuation techniques?
Unlike other attempts to measure intangible assets that are entirely subjective (relying on surveys of managers' and investors' perceptions), the methodology lets the market speak by showing the real relationships between the actual performance of value drivers and performance outcomes. The methodology differs from other measures in its breadth of coverage: researchers examined a broad range of intangible asset categories, in order to identify those most and least important to value creation. And, because the statistical modeling weights each category according to its impact on performance outcomes, it achieves greater accuracy in measuring the individual impact of each driver. The ultimate score reflects real rather than perceived effect.
Data and Process
Overall, when you say you need data for the model, what type of data do you mean?
- Media tracking and content analysis data
- Brand data
- Employee survey results
- Customer/consumer survey results
- Investor ratings
- Corporate social responsibility data
- Financial performance metrics
- Number and type of strategic partnerships
- Number and type of patents and other intellectual property
- Company ratings and rankings
What outcome measures/data do you want?
In terms of financial performance outcomes, Revenue, Share of Market, Stock Price, and EBITDA are prime candidates. Segment level data seems to work better than company totals and since this required for investors, should be available. Multiple measures are not available for these, revenue is just revenue, but segment-level data substitutes. When segment-level data is not available, then regional results might be a substitute.
Non-financial performance outcomes include employee turnover, employee engagement, and customer loyalty for example.
What media measures do you want?
Ideally we will have story counts, impact or circulation, and tone (positive/negative). Categories might include: Customer Relations, Supplier Relations, Legal, etc. – it depends upon the business you are in. Sometimes we only have an aggregated impact score which is some combination of circulation, tone and prominence/ memorability.
What other measures/data can you include?
Other factors can influence our outcomes apart from media. Some of these PR factors might work through and others might work independently. For example, PR likely influences Customer Satisfaction to some degree because PR sets expectations. Yet, the customer's actual experience is most important. Good candidates for inclusions would be: customer satisfaction, retention rates, advertising spending and exposure.
What about competition?
Positive competitor PR usually has a negative effect on our client results, but not every competitor is equally important. When media and other measures are available, we can use them in the analysis.
Do you want quarterly or monthly data for the analysis?
Monthly data is preferable. However, some data is only available quarterly, such as quarterly revenue. The idea would be to have data for several years. The longer the time period is the better. However, more measures in the same categories below can compensate for having a shorter time frame. For many projects, two years of overlapping data is the minimum needed, such as 2004-2005 for every measure. In such situations as this, it useful if and applicable to the analysis if longer time periods in some categories are available.
How can you model with so few data points?
The number of data points influences precision. The fewer data points, the less precise our estimates become. This occurs because any single measure contains error. Some of this error is random error (due to uncontrollable influences outside the model), some is due to sampling (we only see a few time periods) and some is due to measurement error (any single measure regardless of time period is more or less accurate). Using a longer time period, using more robust estimation methods, and using more measures can control all of these errors.
How do multiple measures help?
Using multiple measures (e.g., the collection of segment level data points) allows us to create a more accurate model and analysis. For example, when we use segment-level revenue for example, presumably each segment's revenue will be affected by random error, sampling error and measurement error differently. So that a composite score using segment-level measures will eliminate some of the error. Using the total company revenue, however, just hides these errors in the total.
How do you estimate effects?
In general we weight any single measure in its composite by its ability to predict the values of the important outcomes. The impacts are estimated using a robust weighting method in the context of a structural equation model (also called an structural econometric model).