Prioritizing Analytics for Smarter Decisions
By Why an ‘Analytics-First’ Approach is Essential in Today’s Data-Rich World
In our current landscape of data overload, the value of an analytics-first approach has become paramount. It’s about using the vast wealth of available data to drive new results and create impactful enterprise insights. Proactively participating in and responding to disruptions, rather than merely reacting to them, is central to a dynamic business environment. Being able to respond quickly to market changes, emerging technologies, and customer expectations is crucial for making the most of limitless data. An ‘analytics-first’ approach helps any business adapt quickly to change and emerging technologies. Real-time data analytics and capabilities can extract value from information faster than ever before – a fact that shouldn’t be sidelined in digital transformation.
With technological advancements, it’s cheaper and easier for companies to gather and collect data. However, the real challenge lies in pulling actionable insights from that data to solve business and industry problems and spot emerging trends.
For instance, retailers routinely gather customer data to understand preferences, transaction frequency, and location. While these insights are important, they can also be used more effectively to drive operational efficiency, rather than just being an afterthought of customer actions.
Business leaders must foster collaboration and see these insights as a requirement for transformation. By doing so, they can provide clear directions across the board, driving analytic insight efficiently and reliably. It’s truly about a change in mentality and philosophy regarding how companies view analytics.
Create Your Design with a Holistic Approach
Having real-time data access and advanced analytics at your disposal offers opportunities for your organization to realize the value of that information faster. Yet, too many organizations fail to combine advanced analytics with operational management. The key to solving this conundrum lies at the design level: approaching analytics holistically, rather than as a tool to address an isolated issue.
Consider what kind of information an entire operations team will need and design a common information model accordingly. For example, in a finance scenario, instead of just thinking about what information an accounting team needs for cash management or accounts payable/receivable reports, consider the needs of the whole team, providing more than just pure analytics.
When any system is slated to “go live,” an analytics-first approach helps maintain timeliness and stay on target. Unfortunately, too many companies typically focus on process-driven transaction systems, continuing to gather data without consideration for analytics. By combining real-time data and analytics, companies can see the advantages of bringing more insight into an organization and applying that during a “go live” implementation.
Transformation leaders are finding they can mature projects much faster than before and have more access to virtualization. By combining an information model with real-time data and analytics, companies more quickly realize if they have the necessary tools to track and measure their business.
Information Remains Central
By leveraging technology, improving business processes, and embracing automation, the data and analytics process continues to evolve and move forward. Companies are better able to consistently and constantly measure internal processes with fast access to information, and more importantly, they gain the means to quickly pivot and improve their business.
When considering any enterprise resource planning (ERP) system, it’s not just about creating a slightly better version of the system you already have. By making analytics a priority, you can profoundly affect the flow of how a company operates, thereby envisioning the value and advantage of a new technology program not just in a single process, but in a more holistic way.