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Data analysis tools don't create data-driven culture

Businesses want to be more data-driven, and vendors are capitalizing on the demand with sleek, self-service tools. But it's culture, not tools, that creates a data-driven organization.

Analytics vendors are betting heavily that easy-to-use tools will increase adoption within organizations. Just in the last few months, my inbox has filled with press releases promising products that "bring analytics to the masses." They all propose to solve the problem of low analytics adoption within a company by making the data analysis tools simpler.

But, it seems to me, the tools aren't the problem; it's the culture within organizations.

The acknowledgement from vendors that people prefer, and are more likely to use, simple tools is not new -- and it's obvious. Granted, the tools released today are likely much easier to use than those that came out 10 or 15 years ago. But even as tools become simpler, adoption hardly improves.

There's a general adage I often hear from analytics professionals that adoption of data-driven tools typically tops out at around 20% of a business's total workforce. This is a number that holds pretty steady, regardless of the tool that the IT department or analytics teams give workers.

20% ceiling hinders data analysis tools

Hard evidence seems to bear out this number, and, in some cases, actually makes 20% look like a generous estimate. In the latest Wisdom of Crowds BI Market Study from Dresner Advisory Services, nearly 40% of the firms surveyed said fewer than 10% of their workforce use data analysis tools. More than 20% of respondents said penetration was from 11% to 20%. Less than a quarter said penetration was more than 40%.

One pixel Claudia Imhoff on analytics-driven orgs

What's really remarkable about those numbers is that they are down from previous years, which means that even as tools are undeniably getting easier to use, front-line workers are not embracing them at any higher rates.

There are plenty of reasons why front-line workers may refuse to embrace new analytics tools. For one thing, people don't like changing the way they do things. Along the same lines, people aren't going to embrace new approaches if they don't see a reason to do so. A marketing manager, for example, isn't going to start using a shiny, new, self-service analytics tool just because it's plunked down in front of her. It's up to the analytics team to explain to her how it will help her segment customers more effectively, or test and compare various campaigns to find the most effective one.

Data-driven companies endorse data users

No tool is going to remake workers who currently do not utilize data into data hounds.

But it's more than education. It's up to executives to instill a data-driven culture, and this process is decidedly unrelated to analytics tools. Workers need to know that they are being judged on how well they use data and that, to get ahead within the organization, they are going to have to become more data-driven.

Among companies I've talked to that have been successful at developing such a culture, I hear similar things: People who don't have data to support their assertions in meetings get less time to talk. Management monitors who logs into tools and considers it a performance indicator. Managers practice what they preach, letting data supplant their own gut instincts. This process is something management needs to lead.

So, for business leaders who think they can simply install one of these easy-to-use data analysis tools and, all of a sudden, have a data-driven workforce, it's important to reconsider. No tool -- no matter how simple or user-friendly -- is going to remake workers who currently do not utilize data in their day-to-day tasks into data hounds. For businesses looking to bust through that proverbial 20% ceiling, it's important to take a look at how culture is holding you back and how changing that culture can really take you to new heights.

Ed Burns is site editor of SearchBusinessAnalytics. Email him at eburns@techtarget.com and follow him on Twitter: @EdBurnsTT.

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This was last published in August 2015

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What are your tips for increasing adoption of data analysis tools?
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Don't make it about the tool - make it about the problem that the tool can solve. Case studies can help. 
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The problem isn't necessarily the culture. That excuse is generally "code speak" when IT doesn't understand the nature of the problem at hand well enough to craft a proper solution. That's why vendors are pushing hard on self service BI. It's to try harder to remove IT as a barrier to solving the problem, when IT should be a subject matter expert in high demand.

There are a number of principals that need to be in place before you rush to a solution:

a) IT needs to know the business. That doesn't mean know the products and services, but how and why they are delivered. The strategies (current and past) the business uses to improve overall results. IT professionals who are subject matter experts in the technology but not in how to apply it are a dime a dozen, and they need to know that.

b) The solution strategy needs to be agile. That means changes on the fly and exploring new ideas. IT should respond daily to new requirements, testing, validating and expanding on ideas as they are developed, not on some long development pipe line.

c) You need a devotion to correct information. Bad data is not an end user problem, it's everyone's problem. Bad data leads to bad results every time.

d) Design means making choices. You start with an endless list of possibilities and you whittle it down until you hit your target audience. Few people can (or have the time) to deal with all possibilities. Use your business knowledge and make the choices necessary to get to the correct answers faster.

An ultimately, we need to get smarter at finding the answers that matter. We have to target insights that provide a significant impact and can be acted upon. Too often projects spend months designing reports for which have no next step associated with them. If you can't use the information, then it probably doesn't matter.


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To increase adoption of data tools, it's important to have leadership drive adoption, but also to demonstrate the effectiveness of the tool to lead adoption.

People will do what they are incentivized to do, so demonstrably rewarding those end users who drive effective use of a new tool will pull others toward adoption.

Additionally, create infrastructure (newsletter, email notices, scheduled training/feedback sessions) that reiterate how to use the tool, why to use the tool, and provide best practice insights.

If left to lay dormant, the tool will, well, lay dormant.
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Sorry, every I see IT's failure to add value to the process kicked to management (to drive adoption) it drives me insane. Check out any tool / technology (CRM, BI, DR, etc.) and you'll always see this requirement. IT always wants / expects management to do more for them, like children arguing over a toy.

a) Does the solution drive the business goals? This doesn't mean did it meet the documented requirements, but does it grow the business. If it does and people understand that, you can be assured management will drive it forward.

b) Do it help people with their personal goals? For example, can IT make heros out of business people, without taking a bow themselves? If the business can look / appear smarter, they'll camp out at your desk to get access.

c) Can you drive business value? Not can you drive the tool, but get measurable value from it. All you have to do is pull 3 cool facts no one else knew, and they'll be demanding to know why you haven't rolled it out. If you can't drive any value, do you really expect the business to waste their day banging away at it?

Understanding value and building on that is hard work, one we hope to leave to the business. (IT's view typically is they implement and train on technology, only the business understands value.) But value comes from leadership and if IT wants to lead, they need to spend more time creating value first.

So:
- Save people time
- Make their day easier
- Make them (not you) smarter
- shine a light on the less productive areas of the business
- demonstrate how to use information to create action plans.

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