How to use Analytics to Derive Business Data Insights

What’s your plan for the data you’ve captured about your business?

Capturing business data is one thing, and using it proactively to make business decisions is quite another.

With the advent of the Big Data era, we’re seeing an explosion in data capture tools and systems. But how many of these systems can actually help stakeholders derive any actionable insights from the data collected?

Finding value in your data:

Data is valuable only if it can be translated into insights. And to derive these insights, you need to first find out what’s valuable in your data. Going through reams and reams of reports is counter-productive. Many organizations are still struggling to see insights clearly through their data. How do you arrive at a distilled version – or the essence of valuable data?

Turning data into useful information:

The key to turning data into useful information is to recognize and articulate exactly what you want to achieve with that data before you start capturing and storing large quantities of data.

It’s important to put a context to the data – which means, asking yourself why this data is important, what factors of the business could this data affect, who are the stakeholders who may be interested in this data? It also means establishing why this data is needed – what could be accomplished if this data is provided, which teams may benefit the most from the availability of this data? Too many companies initiate big data projects – or at least projects which use large data – only to end up with not-so-impressive results at the end of the project. To avoid this, it is imperative to anticipate the outcome before you start a data analytics project. Pinpoint how the success of the project would be measured and elaborate on how results will be used or integrated into the business.

In other words, have a well-defined long term plan and clear goals for the data project you undertake; once you have clearly defined the purpose of why you are collecting and storing data, you can go through these next steps to put that data to use in making improvements in your business.

1) Consolidate data from disparate sources:

Ask yourself: what are the various sources from which you could collect data about how your customers are interacting with your products and services? For example, if you sell your products or services online, then online transaction data from e-commerce systems, online marketing data, and data from social marketing platforms, as well as logistical records from warehouses and shipping companies, may all be valuable sources of data.

For some businesses, it may be data from manufacturing shop floors or from remote sensors that is important. The point is that all businesses need to collect data from various systems — including ERP, CRM, finance, etc., — and from various types of applications.

2) Validate the accuracy of your data:

Raw data, collected from various sources, needs to be cleansed and prepared before it can be made ready for analytics. You need to consider how the data was collected. For example, is the data clean or could there be flaws in the collection process? Is it accurate and consistent? Also, is it in a standardized format so that it can be compared or aggregated with data from other sources? Last but not least: is the data that is collected relevant to the goals and expected outcomes of your long-term data strategy?

3) Understand your business processes:

It is important to gain a very good understanding of the various processes and practices followed by your organization in various aspects of the business, whether this is in terms of regional, local, or international best practices, compliance regulations, or legal and government procedures. This helps in gaining better insight into how data analytics can help in business process improvements.

4) Develop high-quality tooling, IT infrastructure, and human resources:

The IT infrastructure that your organization adopts, invests in, and has expertise in, is also one of the factors that will determine whether you will be able to generate high-quality actionable insights. Tools and systems, hardware and networks that collect, store, process, and analyze data need to be of high quality. Of course, the quality of the teams involved in various aspects of data management and analytics also influence the quality of insights derived from your business data. Organizations that pay close attention to making sure that the quality of all three of these is high, will reap rich rewards from their data investments.

Deriving meaningful insights about your customers and your business:

Once data sources are consolidated, the data can be structured to create a single version of the truth and analysis can be performed; only after that can business data insights be gleaned.

Gathering business data insights refers to the process by which you actually put data to work for your business.

Analytics helps you transform business data into information that can be used to optimize your business processes and understand your customers better. It helps you enhance the level of understanding you have about your business.

Analytics also provides you with information that can eventually help you gain ideas or insights into how you could improve business performance.

What exactly are “actionable” insights?

First, let’s look at how we may define an insight. An insight is basically an understanding you gain about how your business is really working — as against how you thought it works — before you accessed the data-driven insight.

An insight makes you rethink your business processes in a slightly different way or consider factors you may not have considered before. Often this kind of a data-driven insight is what organizations are missing out on when they try to derive real business value from data investments.

However, it is not enough to gain insights; the insights must also be of a high quality and must be “actionable”, which means you should be able to closely tie them into your KPIs or direct business goals and effect real changes in performance by using the insight to drive some clear action or change. 

Finally, it has been found that the biggest gains can come from making data insights available to teams that have never had access to data insights before — or those that were either functioning by gut-feeling or by standardized procedures. This is where real business value can be expected from business data insights.

Sound complex? There’s help at hand:

There are a number of data analytics and data visualization tools that can help you to gain insights from business data and analytics. Many of these tools allow you to connect different data sources or import data from external sources, perform analytics on the data, and then visualize the data in easily digestible dashboards and visual reporting formats. This makes it more likely for stakeholders to see patterns in the data that point to trends or insights about what improvements need to be made to improve business KPIs.

Augmented business intelligence tools use AI/ML technologies to automatically uncover hidden trends in business data and drill them down into actionable insights.

Today, a number of data analytics tools and technologies are available in the market that can blend multiple types and sources of data, whether it is through importing data from different cloud or on-premise systems, or by allowing imports of offline spreadsheets containing manually collected data. Most of this new-generation, advanced data analytics platforms feature easy-to-use drag and drop interfaces that can help any employee access and visualize data and have it brought onto customized dashboards and crystallize it into actionable business data insights. These are also referred to as automated insight engines.

In conclusion: Business data insights translate into business success:

The secret sauce, then, is knowing how to make your data work for you!

So, if data is critical to gaining an understanding of how to improve your business, it becomes imperative to foster a culture of data-driven decision making in your organization. What’s more important is that this should be encouraged at all levels in the organizational hierarchy and not just at the top management layers for it to be truly effective.

In most organizations, unfortunately, business data access is restricted to certain layers of management or within certain departments. This requires a big change in attitude towards data security and accessibility. 

Making business data available across the organization will encourage the use of data-driven actions to measure key business success parameters.

Finally, if you are making decisions based on your data, your insight may be limited by your ability to capture, store, process, and manage data. In other words, your data-driven decisions are only as good as the quality of your data.

Remember that, in the end, it all comes down to the quality of your data. Without high-quality, well-integrated data, the foundation of your data-driven decisions is on shaky ground.

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