The PAFTCIG model identifies the four fundamental components of any business – people, assets, finance, and time. These collaborate together to produce information which, in turn, requires governance. Information, typically in the form of digital data, is one of the most crucial business resources of all.
The amount of data today’s enterprises generate is vast, and it continues to grow. Many large companies have already reached the petabyte scale, with the average enterprise data volume expected to reach two petabytes in 2022. This enormous wealth of digital information is spread across an increasingly wide spectrum of platforms ranging from cloud repositories to internally managed and third-party data systems.
The remarkable proliferation of data is a result of the fact that most organisations now capture all data generated during their routine operations. This includes every customer and employee interaction, system logs, databases, and more. When you consider how the four fundamental components of any business – people, assets, finance, and time – collaborate to generate information, it is easy to see why the sheer quantity becomes a major challenge.
Modern big data analytics solutions are essential for making sense of it all.
What are data analytics?
In the old days, businesses relied on spreadsheets full of numbers that needed to be manually examined to reveal trends and insights. Such processes have become woefully inadequate in the era of big data, hence the growing importance of visual data analytics powered by machine learning solutions. These platforms help decision makers make sense of massive data sets at practically any scale.
Data is just information in digital form. To that end, it can help businesses better understand what works and what doesn’t – whether it’s how a certain machine or other system performs, how visitors interact with your website, or something else entirely. However, data holds little value in its raw form, hence the reason we need data analytics to unlock its potential. These solutions translate the raw data into an easily digestible visual form, such as pie charts or bar charts. This makes the data actionable, giving you the opportunity to leverage it to continually improve your operations and grow your business.
Here’s a breakdown the main benefits of data analytics:
1. Deliver a personalised customer experience
Today’s customers expect instant gratification, thus businesses need to be able to react fast and cope with the volatility of customers engaging with myriad touchpoints. To that end, they need to be highly responsive if they’re to make customers feel valued. Advanced analytics make this possible by giving you a big-picture, real-time view of how customers engage your business throughout the buyer journey. That way, you can better understand their needs, attitudes, and priorities and act promptly upon those insights.
The same also applies to employees, which is why larger enterprises sometimes refer to their employees as internal customers. For example, when deploying new systems and processes, team leaders need real-time insights into how employees engage with them in order to know what works and where there is room for improvement. This is why data analytics should ideally be applied throughout your organisation and all of its departments and operations.
2. Identify performance bottlenecks instantly
Performance monitoring is a core area of data analytics and one that becomes exponentially more important for larger businesses with many different systems and processes in operation. For example, manufacturers need real-time performance monitoring on shop floors to ensure their machines are always performing optimally. The same applies in healthcare, aerospace, or any other production-focussed organisation.
Data analytics should also be applied to monitor the performance of teams and services. This applies in any business, especially those with large teams and distributed workforces. Mission-critical services, such as websites, web apps, and other IT systems, should also be monitored continuously to identify bottlenecks and proactively prevent costly downtime.
3. Consolidate your data sources to eliminate silos
One of the biggest difficulties in making sense of enterprise data is that it tends to come from a large and disparate range of sources. Furthermore, most data exists in an unstructured form, which is even harder to make sense of without the application of powerful machine learning algorithms.
Data analytics should provide a holistic view of your business performance across all activities by consolidating data sources – of which there are often hundreds of even thousands. All data of value must be identified, curated, and harmonised from across multiple channels before it can become useful for analytics. That’s why any comprehensive data analytics solution should offer support for common database formats and other sources.
4. Continuously enhance operational efficiency
Data analytics are either delivered in real-time or retrospectively. Both are important, as real-time performance metrics let you instantly detect problems and in-the-moment opportunities, while retrospective analytics leverages historical data to help identify trends. Armed with these insights, business leaders can make informed decisions that continuously enhance efficiency across every domain.
Modern data analytics platforms are typically cloud-based, which means insights are available anywhere on any internet-connected device. This means leaders can make decisions at the speed of their business, rather than having to wait for reports to come in over days, weeks, or even months. After all, a lot of data is most valuable at the moment of its collection, as that’s when it’s most relevant.
5. Foster an organisation-wide culture of success
While the ability to make important decisions in less time is a clear benefit of data analytics, it certainly doesn’t stop there. For a more agile and adaptable business, you also need the right data. Business agility is as much a product of the quality of insights as it is about the speed at which they are delivered. This is why enterprise-grade big data analytics tools must be tailored to align with the unique needs of your business. Indeed, the ultimate goal is to leverage data to define and meet strategic business goals.
These benefits combine to help drive an organisation-wide culture of success. There’s also a psychological factor at play – when teams can see how their efforts are paying off by knowing instantly what works and what doesn’t, chances are they’ll be more motivated and productive. Moreover, computers aren’t prone to human error, and data doesn’t lie. That means there’s less chance of conflict, a reduced risk of operational siloes forming, and a much better chance of everyone being on the same page in pursuit of a common goal.
C-DASH is an intelligent dashboard that gives business leaders a holistic view of what works and what doesn’t across their entire operational environment. It is a core component of the ContinuSys integrated business management system. Sign up today to start your free trial.