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The Analytics Maturity Spectrum

There is no doubt “Big Data” has taken the tech world by storm. I have spent much of 2013 talking about analytics and data science with people all around the US, going to conferences like Strata, and immersing myself in this world for the last 12 months. Over the course of this journey, I have started to notice some patterns about how various people in various kinds of organizations understand and invest in analytics.

The analytics led company is a concept I will define here as a company that seeks to use analytics (predictive, prescriptive, or descriptive) as one of their chief competitive weapons. The canonical example is Amazon, whose use of analytics is part of the DNA of the company. However, there are other more traditional companies that are analytics led, such as Walmart, Proctor and Gamble, Kohl’s, and dozens of others.

In companies that are analytics led, analytics capabilities are spread throughout the company. They are not siloed off to some group in IT that does “analytics stuff”. Such organizations, knowing that analytics has to be a core competency of the company, invest in people - data scientists, data engineers, data savvy analysts and developers, and free them to use whatever tools and techniques are required in order to generate business results.

The next category in the continuum are analytics aware companies. These organizations see the competitive threat. Many may be piloting technologies or starting to do some discovery work in small areas. They see the value, but have not yet integrated analytics into the DNA of the company and made analytics something that would be considered business as usual. These organizations often have a siloed group doing experimentation, and this siloed group often has ties, or is directly part of, the traditional IT department.

Further down the spectrum are analytics ignorant companies. When a company simply does not see the value of predictive analytics, and rather seeks to gain competitive advantage through other means. Finally, at the other end of the spectrum, are analytics hostile companies. They may have sought to use analytics and failed – and then soured on the idea. They may have a technology hostile culture in general. Regardless of reason, they make very good targets for analytics led companies that seek to steal marketshare.

From Analytics Ignorant to Analytics Aware

Most industries, though not all, have had the emergence of at least one new competitor who has used analytics to achieve some sort of competitive advantage. Whether it's organizations like Progressive Insurance who use analytics of how you drive via its Snapshot tool to allow for better underwriting, or it's one of the many online and offline retailers who are using analytics to understand or predict customer behavior, if you are the CEO of any industry where one of these upstarts have emerged, you have likely at least made your executive team aware of the threat.

That said, in industries that tend to be less competitive, due to either higher barriers for entry or presence of a monopoly – the urgency for analytics is much less. These types of companies, utilities, some telecoms, and a few others, means that even if the potential for additional profit is there, the lack of urgent need tends to move analytics to the back burner. It is only when a competitive threat from a related industry emerges (i.e. Google cutting into the Yellow Pages revenue) that such organizations move from Ignorant to Aware.

Moving From Analytics Aware to Analytics Led

In analytics led companies, the approach towards data science will generally be to build the capability in house. Leaders of such companies understand implicitly that analytics is deeply business relevant. They know that predicting customer behavior and anticipating customer needs – and most importantly – connecting those insights to the rest of the business – drives profit margin, customer loyalty, and numerous other outcomes that are core to mission.

Analytics aware companies, on the other hand, will tend to know they need those outcomes, but do not have the capability to achieve them. They often try to achieve analytics by purchasing technology – usually applications that have some analytics capability. While this approach can help the company at least get to level compared to their peers, they do not allow a company to exceed very far beyond their peers, as if one company can purchase a product that does analytics, so can competitors. There may be a short term advantage, but it isn’t sustainable.

Some analytics aware companies may seek to purchase the capability either through acquisition – buying a company that is analytics led and hoping that the new company unit will enable the entire organization to also be analytics led. While such moves have a better chance of providing competitive advantage than buying a product, it is risky, as this pattern tends to lead to siloed analytics capabilities within a business unit that used to be the old acquired company, unless the acquisition is properly integrated (which seldom happens).

The Opportunity at “Analytics Aware”

Data science will obviously be more valued in organizations that are analytics led. However, the most interesting opportunities for change tend to be in the organizations that are analytics aware. The analytics aware organization is the class where the value is understood, but a brand new culture about how to leverage data in new and interesting ways can be fostered. In analytics led organizations, especially ones that have been analytics led for quite some time, certain conventional wisdom may already be in place about what is possible and what isn’t. Often, such “wisdom” constrains the idea-space, causing the most ambitious ideas to sound too big, audacious, or disruptive to be viable investments.

On the other hand, analytics aware companies have experience spending large amounts of money on product and acquisitions. Such costs tend to dwarf what the cost of a competent data science team would be. One can take the budget that is spent on tools and acquisitions, redirect it towards an innovation lab that serves business line leaders, and get a far superior return on the investment.

What is the takeaway of all this?

Do not despair if you are not analytics led…. yet. Use it as an opportunity to redefine the kind of analytics that your organization will use, an opportunity to chase more audacious ideas than people with an abundance of conventional wisdom would ever consider.

Learn more about our Big Data Analytics practice. 

Disclaimer: The statements and opinions expressed in this article are those of the author(s) and do not necessarily reflect the positions of Thoughtworks.

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