Six Pitfalls to Avoid when Becoming Data Driven

I have been busy with the second run of Big Data Survey. Now that we are midway through, it is time for an interim analysis of the score on the door. In this article I share 6 pitfalls to avoid when becoming a data driven enterprise.

Hundreds of organizations from a wide variety have already shared their insights. Around 55 per cent of the participants work at organizations of over 100 employees and are a representative cross-section of the data population: 14% is BI Specialist, 11% Director, 10% Marketing Manager and 6% Data Scientist.

# 1 Lack of Vision

Data is definitely still a large theme for organizations. No less then 88 per cent of respondents indicate that the opportunities of data for their organizations are substantial. Remarkably, respondents still think of a strong vision (87%) and support from management (60%) as most crucial for success with data.

Big Data Survey - Success Factors - GoDataDriven

#2 No Data or Poor Quality of Data

When it comes to laying the technological foundation, the data infrastructure, the biggest challenge is making data available (49%) followed by improving data quality (48%). Developing the right skills to setting up data infrastructure (35%) seems to be less of a challenge.

Big Data Survey - Biggest Challenges - GoDataDriven

Do organizations have a central data storage available? With 55% of participants indicating that their organizations have a central data warehouse, there is room left for improvement.

#3 Storing Data in the Cloud Perceived as Insecure

With more and more applications finding their way to the cloud, we were interested to learn what professionals think of the security of cloud storage. Remarkably, 1 in every 5 (22%) participants do not feel that data in the cloud is as secure as data stored locally. Also, 30% of the participants indicate that data within the organization today is not stored completely secure.

#4 No Time Available for Experimenting

Being a data driven organization is not only about data and technology. The supporting systems and processes are crucial as well, according to 46% of the participants. Room for experimentation and an agile approach are vital ingredients for a data driven process. Multi-disciplinary teams are composed of members of different backgrounds, for example technical know-how and specific domain knowledge. Therefore, in Big Data Survey, we asked if IT & Business should work together to facilitate successful product innovation. Definitely, was the clear answer. 67% of the respondents agree totally with this statement, while an additional 22% partially agree.

Besides data, technology, and process, being data driven for a large part is also about the right knowledge and skills. Over 55% of the participants experience the development of the right skills as the largest challenge while introducing a data driven process. While running experiments is essential for innovation, 44% of participants see that making time available to experiment is difficult within their organization. Working in multi-disciplinary teams is also not a given, with 36% of organizations having challenges with this way of working.

Big Data Survey - Innovation - GoDataDriven

Still, 70% of respondents indicate that within their organization there is a reasonable amount of space to experiment. In the last stretch of Big Data Survey we hope to find out if this is really the case.

#5 Static Websites without Personalized User Experience

Looking at the solutions that organizations develop, we see an interesting development. The number of organizations that develop predictive models (65%) is getting closer to the number of organizations that make use of dashboards and business intelligence (80%).

Despite the fact that marketing is the most popular application of data science, only 12.6% of researched websites is actually personalized in real-time. Most websites today are still static (50%), providing a poor and outdated user experience.

# 6 Inability to Attract Data Professionals

Besides the aforementioned data, technology, process and skills, it’s the people that really make the difference. Not every organization employs data professionals, over 54% of organizations says they work with external consultants.

Organizations that recruit their own data professionals need to adjust their organization and working condition to the demands of data engineers and data scientists. A company car or a short commute are no crucial factors to select an employer. What matters most are the room to experiment, a transparent organization and above all: the knowledge level of colleagues that make the difference. Skills attract skills.

This article is an interim analysis of Big Data Survey.

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