The Challenge of Market Data as a Commodity

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by Diego De La Garza

It is no secret that information is power, and companies across every industry seek relevant information in order to competitively position themselves in the market. As a Strategic Sourcing consulting firm, we specialize in finding and processing valuable market data (data) to generate and provide strategic information to support the decision making process of our clients. Although sometimes the terms “information” and “market data” (or simply data) are used interchangeably, they are in fact very distinguishable terms with different implications.

“Information” is the result of processed data, and its value is based on the knowledge it provides to the receiving entity. “Data” is a collection of facts, and its value is measured in terms of how fast and easy can be processed into useful information. Much like a cocoa bean will eventually become a chocolate bar, corporations can look at data as the raw material of “knowledge”, a much more complex product that results from an analytical process.Unfortunately, just like the cocoa bean, data has become a marketable item in high demand, meaning it’s oten treated like a commodity.

Recently, we’ve come across claims that “data is a commodity available to everyone, and those companies who make use of it first will gain a competitive advantage”; however, the premise is partly inaccurate and false for us in the consulting world.

First and foremost, we need to further define what we mean by data. In consulting, the conception of “data” may be different from what it means within financial and economic environments, where data tends to be vast, publicly available, focused on hard metrics (i.e. stock prices, credit ratings, valuation ratios, etc.) and is primarily used for valuation purposes. In consulting, data is much more reliant on soft and qualitative metrics. By data, consultants mean rate cards used by suppliers to render services, the pricing structures of goods, the costs of licensing tools and software, the volume of the operations, supplier performance, the state of the competition, the new trends of the industry, etc. While other sectors may consider these things thoroughly processed information, for us, it is still raw data.

From a strategic sourcing perspective for instance, data is digested differently. Take, for example, a benchmarking exercise where a supplier is evaluated against the market for purposes of ensuring quality service at competitive costs.Our analysis must go beyond hard metrics, in order for us to generate useful information for our client, we must account for delivery and performance, service scope, engagement volume, and overall, define a unique profile of the relationship at hand. Once, all this is clear, the real “market data collection” phase begins, which will focus on answering one (loaded) question: How are we (our organization) doing, relative to the market, and what do we need to know to maximize competitiveness?

On a situation where a rate card for general management consulting (GMC) services is being utilized by a company who wants to determine if their incumbent supplier is offering competitive hourly rates, finding what other GMC firms charge will not be sufficient, we will also need to determine the size of the engagement, the scope of the services, the resource composition, the profiles of the resources and the utilization levels of those resources.

This brings me to my second point, finding “valuable data” is actually not an easy feat, specifically because the “value” of data does not obey typical market conditions. Instead, the “value” of the data is measured under three conditions: accuracy, validity, and most importantly, relevancy. The first two are relatively easy to define. “Accuracy” refers to how correct and precise the data is. “Validity” refers to timeliness and how much the data corresponds to the real world. “Relevancy” refers to how much weight the data will have on the matter at hand. Valid and accurate data is not hard to come by, finding relevant data is a different story.

Let’s take the benchmarking example again. Given that we have an internal understanding of the relationship with this supplier, we will have to find rate cards for the same service with similar GMC suppliers that have the same resource and role composition (accuracy), and ensure those rates are recent and valid (timeliness). Probably easy enough data to gather. However, we would also have to ensure those rates are utilized by direct competitors, under similarly sized engagements (spend levels) and with comparable scopes and deliverables (relevancy); this last component, is the hardest to find.

Lastly, remember that data becomes information by interpretation; therefore, a competitive advantage will not generated by those who get the data first, but to those who can best interpret it. By that we mean taking the facts, the feedback and the indicators and identify where they fall relative to the organization, and subsequently identify gaps and develop strategic steps to improve processes, generate synergies, and manage resources better. Generating a competitive advantage comes to those who can do more with less.

The reality is that market data is, in fact, treated as a commodity – it can be sold, traded, found, exchanged, and even mass produced. It is also true that whomever gets the data first will be able to process it first. But it is how an organization process the data, and the way they use the resulting information, that will generate a competitive advantage. Ensuring “valuable” data (accurate, timely and relevant) is available is as important as having the right tools and resources to process it, otherwise this “hot commodity” will be nothing but a collection of facts stored in the cloud. Much like the best cocoa beans will never become gourmet chocolate unless they first go through the right process.


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