> ## Content Index > Fetch the complete content index at: https://www.thedigitalspeaker.com/llms.txt > Use this file to discover other available public pages before exploring further. # Five Signals Your Organization Is Ready For Big Data - URL: https://www.thedigitalspeaker.com/five-signals-your-organization-is-ready-for-big-data/ - Published: 2015-02-13T00:00:00.000Z - Updated: 2026-08-04T05:37:45.000Z - Description: Developing a Big Data strategy is not easy and not everyone is ready for Big Data. These 5 signals indicate that your company is ready for Big Data. - Author: Dr Mark van Rijmenam, CSP - Tags: Strategy To start or not to start with [Big Data](https://www.thedigitalspeaker.com/big-data-speaker/)? If you are a competitive organization that also wants to remain in business the coming five to ten years, the answer should be clear. But when is your organization ready to start with Big Data? When is everything in place to successfully develop and implement a Big Data strategy? When are you set to embark on the Big Data challenge? During my work as Big Data strategist I came across five signals that indicate that your organization is ready for Big Data: ## 1) A Shared Understanding of Big Data Exists Within Your Organization If there is no shared understanding of what Big Data can do for your organization, it is of no use to start. Big Data means something different for every one, every organization and every industry. There are so many possibilities with Big Data and if everyone in your organization has a different idea about what it means, it will be difficult to get everyone aligned and to successfully implement a Big Data strategy or to at least start with a Proof of Concept. ## 2) Business Intelligence Is Part of Decision-Making Processes Starting with Big Data will become very difficult if you have no data-driven culture at all. Your organization should at least have some sort of Business Intelligence in place, to monitor how the organization performs. You should have established KPI’s that are monitored on a constant basis and some of the key processes should already be analysed regularly. In other words, you are already using some of the data available in your company and you have some sort of data-driven culture that requires managers to use BI reports in their decision-making. Managers already trust the data they work with and as a result already make better decisions than when they make decisions just based on gut feeling. ## 3) Experimenting and Innovation Is Encouraged When you want to start with Big Data, you should first develop a Proof of Concept to learn what Big Data exactly is and can do for your organization. Big Data projects typically take 18 months to be completed and during this time, results are far from obvious. This however should not be a reason not to start with Big Data. Experimentation and [innovation](https://www.thedigitalspeaker.com/digital-innovation-speaker/) should be encouraged to enable you to learn by doing and discover along the way how Big Data can really help you. If you are not allowed to spend quite some time on something where the results are unknown, you are not ready for Big Data. ## 4) You Work With High Quality Data Poor data quality is for many organizations a reason not to start with data. Simply because poor data quality makes your life, and especially that of data analysts, very difficult. There are several aspects that define data quality: - Standards: are data elements consistently defined and understood; - Complete: is all the necessary information present; - Accurate: does the data accurately represent reality or a reliable source; - Valid: does data values fall within acceptable ranges; - Unique: does data appear several times. Data quality starts with the right Master Data Management practices in place in your organization and this forms the basis of Big Data analytics. When your data is not managed correctly and the quality is not ensured, your data can become a risky liability instead of a valuable asset and any analysis done is useless. Therefore, high quality data is a pre-requisite of a successful Big Data project. ## 5) The Board Understands the Value of Big Data As mentioned, Big Data project do take quite some time to be completed. In addition, Big Data does cost money, while at first results may be unclear. If you therefore want to succeed with Big Data, it is vital that there is board-level support as otherwise projects are likely to be stopped before results can appear. In addition, Big Data remains a people’s question and therefore a cultural change is required. This has to come top-down if you wish to succeed. Therefore, when your management board understands the value of Big Data, you are likely to be a lot more successful than if that’s not the case. Developing and implementing a Big Data strategy is not easy and not all organizations are ready for Big Data. If the above five aspects are present in your organization, you are ready for Big Data and likely you will be successful in the end. Starting with Big Data without any data background is useless and therefore it is better to first prepare your organization for this new way of working. It might be a long process, but in the end it will be very rewarding. Image: [Wikipedia Commons](http://upload.wikimedia.org/wikipedia/commons/9/9a/US%5FNavy%5F070213-N-3729H-225%5FA%5Fplane%5Fcaptain%5Fsignals%5Fan%5FE-2C%5FHawkeye%5Fassigned%5Fto%5Fthe.jpg?ref=thedigitalspeaker.com) ##### *Image Credit:* [*Ditty\_about\_summer/Shutterstock*](https://www.shutterstock.com/g/Ditty%5Fabout%5Fsummer?ref=thedigitalspeaker.com) ## Frequently asked questions ### What are the signs an organization is ready for Big Data? An organization is ready for Big Data when there is a shared understanding of what it means across the company, business intelligence already informs decision-making, experimentation and innovation are encouraged, the organization works with high quality data, and the board understands the value of Big Data enough to support it long term. [Link to this question](#faq-what-are-the-signs-an-organization-is-ready-for-big-data) ### Why is data quality important before starting a Big Data project? Poor data quality makes life difficult for data analysts and can turn data into a risky liability rather than a valuable asset. Data quality depends on standards, completeness, accuracy, validity, and uniqueness, and it starts with proper Master Data Management practices. Without high quality data as a foundation, any analysis performed is essentially useless. [Link to this question](#faq-why-is-data-quality-important-before-starting-a-big-data) ### How long does a typical Big Data project take to show results? Big Data projects typically take eighteen months to be completed, and during this time results are far from obvious. Because of this long timeline with unclear outcomes, organizations need to encourage experimentation and innovation, allowing teams to learn by doing and discover along the way how Big Data can actually help the business. [Link to this question](#faq-how-long-does-a-typical-big-data-project-take-to-show) ### Why does board support matter for a Big Data strategy? Board-level support is vital because Big Data projects take considerable time and cost money while results may remain unclear at first. Without top-level backing, such projects are likely to be stopped before results appear. Since Big Data also requires cultural change, this change must come top-down for the strategy to succeed. [Link to this question](#faq-why-does-board-support-matter-for-a-big-data-strategy)