Insights from Macro Analytics

Measurement is a precursor to improvement. To measure is to analyze, and a basic concept of analysis is comparative assessment of metrics to study trends and relative changes.

Every company should have a well-established list of key performance indicators (KPIs), which are evaluated with periodic frequency. The focus on internal KPIs is an important aspect of developing strategies to optimize performance within the company. This is the micro aspect of managing the business since the majority of these metrics can be controlled or be affected with direct intervention.

On the macro level, there are many external factors that impact company results. Economic condition and outlook, technology, innovation and a competitive landscape are some of the macro factors impacting the performance of a business. These macro factors can be controlled to a lesser extent, and remediation strategies may call for investment in innovation, accelerating change initiatives or rethinking the business model. Remediation measures for macro factors can also call for large capital investments; hence, a well-designed strategy informed by actionable insights is significantly important to the exercise.

Many companies embark upon peer benchmarking, which is an important principle that allows for assessing the factors that may cause differentiated performance in a specific industry. Relative benchmarking offers key insights into the various strategies with which competition may be approaching the market and offers new considerations for management to guide the company’s operations and strategy.

However, these exercises are often conducted as a one-time analytics project whereby a regular periodic review of the competitive landscape is conducted only for periods with extreme movement in a company’s results, usually when results miss expected outcomes. Even at companies that frequently review competitive results, the relative analysis is relegated to review of traditional metrics – financial, operational and other measures available in the public or subscription domain. While this approach is reliable, it does offer a substandard alternative to a more comprehensive study of factors to explain results. Cost, absence of data, relative priorities of business, etc., can pose obstacles to developing a broad competitive analytics view. This leaves a gap in a comprehensive macro analysis of company’s operational environment and, therefore, provides a less than complete picture to senior leadership.

At DHG, we have taken a platform-centric approach to building competitive benchmarking solutions that allow us to identify, procure and transform several variables in order to provide a broad assessment of macro factors that can be studied and correlated to various internal KPIs. This platform-centric approach helps us to leverage our broad industry knowledge and data points to create and study various patterns in the broad economy, an industry or a subsector of choice. While this involves an upfront investment in identification, assessment and development of various KPIs and a systematic approach to obtaining the data points to deliver the KPIs on a periodic basis, the return on investment may be justified by the clarity afforded to understanding the results and informed decision-making for the future. The result is a repeatable, scalable and indispensable platform that can analyze and dissect various pieces of insights to procure attribution of results, with the ultimate goal of finding the causality of trends as well as results.

To determine causality, it is important to consider variables of interest that not only provide a direct view of the relationship between independent and dependent variables (for example, unemployment rate and its impact on credit losses), but also provide a view of underlying events that are causing the phenomenon – for example, trade agreements that are viewed as punitive to specific sectors and regulations that may impact an industry and a geography in an adverse manner. So, while correlation is a good start to determine causality, a broader view of cause and effect needs to be considered to form a view on causal relationships.

To determine causality, one must not only throw a wide net to capture a broad set of variables, but also leverage an emerging set of new and alternative variables that may not have been in the purview of traditional financial and operational analysis. The large amount of data and available analytical channels now provide for an increasing array of alternate KPIs to be developed to ascribe the performance of an operating unit and unlock the stories behind the data when it is co-mingled in new and unique ways.

We recommend considering a platform-centric approach to gather competitive intelligence, in which a wide array of variables is systematically obtained, transformed and leveraged on a periodic basis to provide a holistic approach to understand business results. In doing so, we also recommend looking at metrics outside of the domain of study, as an example – to study financial results, look at non-financial metrics to determine their impact on financial results.

Later in this series, we will discuss how to use alternate KPIs to better understand business results, as well as the micro and macro environments. We will also highlight examples of such alternate KPIs and how companies can develop acute insights by leveraging these alternate variables.

For more information, please contact us at or reach out to the author, Amit Arya, at


Amit Arya
Chief Data Officer


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