Data-driven is quickly becoming the hottest buzzword in tech. Everything is data-driven these days, from decision-making to campaign formulation and production planning. To be data-driven is to be one step ahead; or is it?
When done correctly, becoming data-driven brings a long list of benefits. You can gather insights on key decisions you make – both as a professional and as a business – and those insights will allow you to make better decisions, even in the most complex situation.
So, what does it take to be more data-driven? More importantly, what does it mean to be data-driven as a business? We are going to answer these questions in this article.

More Than Data

Data-driven is actually an adjective with a very specific meaning. Being data-driven means relying more on data and the insights brought by various information sources rather than on experience or intuition. For a business, especially in today’s competitive market, being data-driven means basing every decision on clear data and the results of data analysis.
However, becoming data-driven is so much more than gathering data. It is about relevance and context; there is no point in having a large volume of data if the data is not relevant to the decisions you want to make. Context becomes an important ingredient in the whole process of becoming more data-driven.

Data Collection at Its Best

In order to become data-driven, relying on conventional methods of gathering data is not enough. You cannot expect to have relevant insights that can be used in decision-making processes when using older methods of collecting information.
Surveys, for example, work great for collecting small samples and manageable datasets, but they are not the most efficient data collection method if you need to understand the market as a whole. The same can be said for logs and manual entries for data related to operations.
This is where newer tools such as field intelligence and time monitoring come in handy. There are now data collection suites designed for specific operations and industries. Rhumbix, for instance, is known for its suite of field intelligence tools designed for construction companies.

Planning Is Required

Similar to the implementation of other technologies, data analysis and other solutions designed to tap into more data cannot be implemented effectively without some degree of planning. This is where many businesses struggle; this is also where the main purpose of becoming data-driven gets lost.
As a way to mitigate this challenge, more companies are relying on tech committees or TCs to make better tech-related plans. A tech committee consists of people from different backgrounds. Each member can contribute to the planning process thanks to their specific expertise and experience.
You too can use the TC model to establish better plans for your implementation of data-driven operations. Learn more details about how TCs are very effective – and the different ways you can optimize your own tech committee – to get started.

Provide Access

Everyone, from the CEO of the company to sales executives handling clients’ accounts, needs to make decisions on a regular basis. For the data pool to be effective for the entire organization, the implementation of data gathering and analysis must be followed by the democratization of data itself.
Now is the perfect time to provide access to relevant information to other decision makers in the business, including those at the lowest level of your company’s operations. The more accessible the insights are, the better decisions each stakeholder can make for the benefit of the company.
Naturally, data access needs to be managed meticulously. Fortunately, there is no shortage of systems (and access management features) for handling this task. You can be very detailed about who has access to which data.

Accelerate with Automation

Creating a large data pool and gaining insights from it are tasks that can be done manually when the business you run is relatively small in scale. Start gathering data from hundreds of sources, however, and manual operations of the data pool will no longer be possible.
The solution to this challenge is automation, but before you get to that point you also have to invest in integration. Using the Rhumbix Field Intelligence Platform as an example, construction companies can integrate the platform directly with existing business solutions.
The result is seamless integration; it also enables better automation of features, particularly data filtering and analysis. Instead of manually entering data into the analytics suite, the suite can pull data from other systems like Salesforce and Zoho.

More Implementation Tips for SMEs

Becoming data-driven is both easier and more challenging for small and medium enterprises. The set of challenges is easier to tackle due to the scale of SMEs. There are fewer changes to be made and the entire company is already optimized for maximum flexibility. Leaner teams also adapt to the necessary changes faster.
The real challenge comes from the same source. SMEs don’t have the high budget of larger corporations. They also don’t have large data streams that many bigger companies benefit from when pulling data for analysis. There are a few ways to overcome these challenges as a small business operating from home.
First, you can run your entire data gathering and analysis suite in the cloud. Cloud computing certainly makes data intelligence operations more accessible, simply because you don’t have to invest in computing power to get started. There are even suites already running in the cloud, and you can access them for a small monthly fee.

As for data streams, you have the internet to tap into. Focus on both internal data – from operations and employee engagement – and external data – derived from customer engagement, social media, search engines, and other sources – to create a relevant and contextual data pool that your business can benefit from.
Now that you know the key things about becoming data-driven – and you have the best tips and tricks to get you started – you can start by formulating your own implementation plan and gaining relevant insights about your business. Once the data pool is established, making data-driven decisions is just a matter of pulling the right insights at the right time.


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