Nooshin Yazhari is the president and managing director of Optimum, a modern software solutions consulting firm.
As businesses operate and evolve, data and information should be collected, managed and shared. Businesses must be able to properly analyze their data and turn it into insightful reports so leaders can make informed operational and strategic decisions.
In many cases, disparate data sources and multiple systems of record create the biggest challenges in building up the capability for a business intelligence (BI) platform. Even if they’re presented by way of a fancy dashboard, reports won’t be accurate or reliable without consolidated datasets with clean and aggregated data from your key data sources and systems. Eventually, your users and stakeholders won’t trust or use the data.
A number of solutions exist to tackle this challenge — traditionally, businesses have opted for data warehouses and data lakes, which organize the data in one central location for BI and reporting purposes. However, this option can be expensive and is often considered a multi-year project for many organizations. In addition, many companies may not be able to pull their data together in this way because they work with old systems that don’t allow for easy integration.
Companies like my own specialize in both robotic process automation (RPA) and BI solutions, helping clients assess their current data sources and systems, understand the integration point and where RPA can be applied, define the right key performance indicators (KPIs), and develop consolidated and accurate dashboards and reports.
RPA bots mimic the behavior of a human and can rapidly pull and consolidate data from various sources and applications in a way that expert data analysts do. The bots can be scheduled to wake up, open any application (cloud-based or on-premise), “click” on the relevant screens and options to pull key data into aggregated datasets or push the extracted data directly into another system.
As you can imagine, the RPA data extraction and integration process is much faster and cheaper than data warehousing and doesn’t require the complex programming needed to develop application programming interfaces (APIs), extract, transform, load functions (ETLs) or data pulls. RPAs can connect to nearly any system and pull/push data in real-time, as it behaves like a human, which boosts the speed, quality, and accuracy of your aggregated data — and ultimately, your business intelligence.
Consider these main factors when deciding how to aggregate your data:
1. Today’s business world requires accurate data – and fast.
We live in a data-driven culture that looks to analytics and key numbers for insights, and these methods are always evolving. With the latest BI tools available in the market, companies can quickly develop and deploy advanced and user-friendly dashboards and reports to their internal and external users. However, feeding accurate and consolidated datasets into those dashboards and reports remains the main challenge and shortcoming of those BI solutions.
Businesses should consider the use of RPA bots for rapid data collection, aggregation, and integration not only as a short-term solution, but also in conjunction with their long-term data warehousing goals and plans to spread up the process and cut cost on API/ETL development effort.
2. You need automation.
In most cases, businesses use various applications and business systems, such as customer relationship management systems (CRMs), enterprise resource planning systems (ERPs), project management tools and financial applications, to help them get the job done and connect with customers and users. Some companies create and use a large number of various spreadsheets in addition to those systems to close the gaps and handle the data that sits outside of those business systems.
Manually collecting, managing and sharing that data using spreadsheets and shared folders can be chaotic and hinder productivity. This is where you may benefit from workflow automation capabilities, which are usually part of a good RPA solution, to integrate and automate your data collection and sharing processes, set up notifications and approval workflows, and automate the collaborative work across your teams and systems.
3. Even RPA needs quality data.
Strong RPA products are available on the market that can allow companies to rapidly set up RPA bots that can feed consolidated data into their BI dashboards. I’ve seen this trend emerge in recent years while working with clients.
However, these tools are still only as good as the data you put into them. When consulting with clients, we encourage developing a solid company data integrity and management strategy, properly defining the flow and owner of your key data in the sources systems, investing in data integrity and clean-ups, and applying RPA and other technology to rapidly collect, aggregate, and clean up your data.
As the business world continues to change, ensure that you and your team have the right strategy and plan in front of you to make key BI and automation decisions in the most efficient, cost-effective manner. Clean and aggregate your data into valuable reports and KPI dashboards that will set the right strategy and foundation for your company’s BI. Take the next action steps to develop data and BI strategy in a way that will best benefit your business.
Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?