2.3% and falling...Corporate budget allocation into Data Analysis.

Information is a liberator. Or so it should be. That's what we're told.

So, when the time comes for decisions to get made, it's often with a sense of self-recrimination that we pause, reflect and regularly postpone.

And we're NOT making decisions more and more and more. In a survey conducted by LexisNexis in 2010 it was discovered that the speed to decision is increasing and aligned to an overload of information. With this excess of unstructured data, happiness is easily replaced by stress and we're left with employees spending over half their day sorting data instead of using it. Surprised? In the 7 years since, data has increased 300%. It's not got better.....

The obvious question is of course, "Why can't we make a decision?". Don't we have more data to base our decision on? Shouldn't that propogate a quicker decision? Won't that quicker decision, in some cases, equate to sales wins, operational improvements, money saved?

The answer is threefold:

1. The data we use, even from good verified sources, even from well-built systems, is rarely combined in a way to facilitate good decision making. In other words, the through-put of data is void of strategic intention. The decision-maker has a criteria which is not manifest in the report, dashboard or presentation.
2. Companies have traditionally invested fleetingly in data analytics skills, preferring to allocate budgets towards marketing ventures aimed primarily at finding and retaining customers. According to CMO Survey in 2015 budget allocation into data analysis is down to 2.3% while marketing spend is set to rise 126% to 21.4% this year. The irony here is that the marketing strategies have quickly become digital marketing strategies, with integral Omni-channel analytical support needed to understand the "big data" of customer location and behavior.
3. Data isn't clean. Simple. As we use more data, more questions appear regarding the source, the method of analysis, especially around key growth intelligence like addressable market sizes and shares. These represent costly data and for many in knowledgeable positions, the results are often at odds with "on the ground" experience. KPIs that combine layers of intelligence (GDP + economic risk index + industry segmentation of consumer spend shift) are fraught with opposition, often due to the lack of transparency provided.

So is there a solution?

Yes. But it requires a data intelligence strategy and budgets to be re-drawn. Understanding the industry of analytical support is the first step to building a better-informed section of your workforce that can genuinely represent strategy & planning activities; the second is to invest in third-party analytical support to address the here and now.

Analysis is a specialism and not everyone can be an analyst. Organizations that recognize this will benefit most from a workforce doing their job in the most efficient and happiest way. Although it's simple to say "salespeople want to sell" and "managers want to manage" it is, in essence, true. And, analysts want to analyse things and support the business in their way. But how many businesses are analytically mature? According to PwC in an extensive C-suite survey in 2016, as little as 13%. The only way to change this is to invest, both short-term and long-term, neither of which should be mutually exclusive contracts.

The maxim preceding this article talks of the aim for perfection. In Churchill's case, in a strategy, where action is required, where it is necessary. But the more data provided, the more paralysis sets in.

But it's not really "analysis paralysis". The right people and machines can analyze data, ready for the human part of a business to take over, to use in business relationships, in customer service, and human resources.

It's just a skill gap.

A funding gap.

Let's call it the "analysis gap".

David Porter is the CEO & Founder of TPC - Strategy Consultants and co-designer of PriceMark, the most advanced competitive pricing tool on the market. His experiences throughout strategy, planning and BI teams led him to set up a channel solutions business and now works with global vendors and regional businesses, supporting their GTM and RTM strategies by introducing data models to their decision-making processes.

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