What is Data Insights and Analysis: Advanced Tips

You recognise the importance of data analytics, and you’re in the implementation and usage phase. But, what can you do to reap the best data insights from the information you hold? These advanced tips are designed to show you the power of data and everything you can glean when you approach it in a methodological way and leverage automation solutions to drive your business forward. 

Data is information that typically is formatted as numbers and text. There are two main types of data, namely, qualitative and quantitative. Quantitative data can be numerically measured, and qualitative data can be observed. 

Data comes from all different locations, including forms that users fill out, customer behaviours through their actions taken on websites and apps, survey information, text messages and images, etc. These pieces of information play a role in helping business leaders make the best business decisions to achieve their goals. 

This is because data can be used for customer insights about demographics, user behaviour, preferences and activity. It is also used to understand staff performance, product performance, company performance, and financial performance. In this sense, businesses will know where to allocate their resources like money and time to serve their audience best, and where the risk and opportunities lie. 

The amount of data collected and stored grows every second. As such, not only is it important to leverage analytics to make data useful, but automation tools must be used to collect, store and organise data to be made useful. 

What is Analytics?

With all the data you collect and keep, what is the next step to turn it into insights? This is where analytics come in as they are statistical models and mathematical algorithms that help discover patterns and trends within your data. 

Automation tools can help to separate data into groups. It can also take unstructured data and help to make it structured (organised in categories so that patterns emerge). Let’s take an example from the financial industry. Say you are a bank with a lot of information on your customers. You will need to pull apart their financial data to assess their creditworthiness for a mortgage loan, for example. Automation tools can help assess customers’ expected future behaviours based on patterns from their historical data. 

If you think of pulling insights from data, you can imagine a pyramid structure, with data at the foundation. Data moves up the pyramid through the analytical process to get to the point on top, which is actionable insights. As you know, a pyramid is most expansive on the bottom. Like data, there is a lot of it, but not all of it is unable for insights. So, the analytical process will filter and organise the data that matters to get to the insights you need. 

What is Insights?

Insights are what prove to be of value to your organisation from the data and analytics process. Insights can be equated with everything that was learned, which can then be applied through business decisions and strategies. 

Insights can either pinpoint areas that need improvement within your business, or they can be new pieces of information that will help lead the way towards growth. In actionable terms, you may use insights to allocate funds towards a new marketing campaign or build a new product because you have proven there is a need for it. 

When it comes to gleaning insights, you want this to happen promptly. Processing massive amounts of data and running analytics can be done with the help of artificial intelligence and automation solutions like SolveXia. SolveXia will transform your data into automated reports in real-time so that you can make swift and agile decisions, backed by data. 

The Connection - Achieving Actionable Insights 

Just like not all data is created; equally, not all data is equally useful to create actionable insights. However, there are many characteristics of insights that make them actionable. Here’s how you can leverage the right data to create the answers you seek. 

• Alignment: You want to make sure that you measure data that is relevant and aligned to your business goals. One way to do this is first to define your business goals and objectives. Then, you can choose key performance indicators (KPIs), or metrics to measure that is directly in line with said business goals. You want to make sure that you measure aspects that are within your control and in areas, you can focus on if you need to make changes. For example, if you want to grow revenue by 10%, then you’ll need to focus on measuring monthly sales. 
  

• Context: Insights from data are dependent on its context with other data. To illustrate, if you’re trying to grow sales, then you need to judge your future sales over previous weeks sales. If you’ve just implemented a new marketing ad campaign and sales don’t change from the week before, then the context would show that something isn’t working and lead you to take action to change the marketing campaign. 
  

• Relevance: While data doesn’t lie, the interpretation of information can be infused with subjectivity. For this reason, data must be directed to the right person at the right time. Decision-makers need data and insights in real-time so that automation solutions can provide automated reports to top-level executives promptly. 
  

• Specificity: You need to know why something has occurred, not just that it happened. If you see that sales boosted randomly, then it may seem fishy or be at the hands of fraud. That’s why insights are most useful when they are specific and complete. 
  

• Novelty: The collection of data and analytics practices can be iterative and endlessly repetitive. This is a big reason why robotic process automation is a perfect solution for big data. That being said, having new insights arise can be exciting because it can drive a particular curiosity. This will allow people to get involved and ask questions, having a genuine interest in what is behind the change in data. 
  

• Clarity: Like any information, it can only be used if it is adequately understood. This is where communication and visual representations can come in handy. The right data visualisation tools and messaging must be sent to the right people so that the insights prompt proper action. 
  

Analytics for a Business Goal

Businesses use data analytics to achieve their goals. Analytics can be used to help accomplish any business goal, be it to grow revenue, boost customer retention, detect fraud early on, adhere to compliance regulations and so on. 

Data automation and analytics tools like SolveXia help you to achieve business goals by answering questions on why a particular plan of action is or is not working. Analytics methods can tell you what happened in the past, showcase the current status of operations and help you to forecast the future. All of these analytics will help you to make well-informed decisions to achieve your business objectives. 

How to Turn Data and Analytics into Actionable Insights 

Moving data analytics to actionable insights requires a mix of human intervention and automated solutions. At the forefront, your human resources can come together to define what your goals are and choose what to measure. Then, you can let automation tools do the heavy lifting and behind-the-scenes work to deliver you with the information you need to take action. 

Find your inspiration

Measure the right things: When you have your defined goals, you can brainstorm what needs to be measured. Every business is different, so the measurements need to be directly in line to get you to your goal. ‍

Ask the right questions: Ask the right questions to the right people. This means getting your team involved and also including stakeholders. 

Do your homework

Use segmentation to drive action: Break up your audience based on data so that you can deliver their tailored needs directly to them. 

Use clear visualisations to convey a message: Looking at a whole bunch of numbers without a story can cause confusion. Be sure to pick the right visualisation tools to help stakeholders and decision-makers understand what needs to be done. 

Discover the context: Like an architect, you get to build your insights as you need them. You can filter, group and sort information based on its context and relation to the business goal. 

Visualise

Be aesthetically mindful: No one wants to look at a messy report. With an automation tool like SolveXia, you don’t have to be a designer to create a visually appealing report. Instead, you can use the library of templates and customise them on an as-needed basis. 

Build an optimisation plan

Focus on trends, not data points: To take action, you can’t get too bogged down in the small details of data points. Instead, you can visualise overall trends (especially when they change direction at inflection points). 

Compare time ranges: When you break down insights based on a weekly or monthly basis, be sure to measure the same time ranges. For example, each month has a different amount of days, so you should account for that. 

Search for strong relationships: Based on the patterns you see, you can come up with a hypothesis for why something is happening the way it is.  

Try different perspectives: Integrate both data sources and people to get new perspectives on the information you reap from the data. 

Be sceptical

Break down organisational silos: Before you take action on data, be sure that it’s accurate and tells the same story every time you run a model. With manual data entry and storage, you run the risk of having organisational silos and missing information. That’s why automation tools can pull data from various sources and ensure its veracity before using it for analytical insights. 

Hire smart people: Automation and analytics don’t remove the use of people. Instead, they augment the ability of your team to make them stronger and more informed. Always hire people who are open-minded, well-rounded and able to critically think about the insights they have in front of them. 

Build a Culture of Data/ Continuous Improvement

Since organisations get new data every day, the process of data analytics and using insights doesn’t have an endpoint. Instead, you have to build a culture that works and easily adjusts according to what the data says. 

This may come with some pushback, but it doesn’t have to. You can get your organisation on board for operating this way if you teach the benefits of using data automation. A team can buy into continuous improvement more quickly if you can: 

• Link performance to metrics: When you assign roles and responsibilities, work can be assessed based on metrics. Communicate how success will be measured and what KPIs will reflect performance. 
  

• Remove barriers to data: With a centralised system of data, you can grant access controls to those who need to use the data and information. Removing silos and barriers promotes a culture of transparency and collaboration. 
  

• Use dashboards to meet agendas: Everything that is measured can be managed. When you set your business goals, you can build and customise dashboards to continuously measure everything concerning the goal. That way, you can always see if you’re headed for success or if you need to change course. 
  

Let Automation Tools Do the Work 

It cannot be overstated how essential automation tools are when it comes to data insights and analytics. While people can manage data manually, it is rife with errors and becomes timely and overwhelming. And, with big data, automation tools are necessary to perform analytics in real-time. There’s just no other way to get it done with such speed and efficiency. 

Automation tools such as SolveXia’s include:

• High-value data: Helps to collect the correct data within context. 
  

• Modelling and analytics: Continuously run models and reap the benefits of analytics promptly. 
  

• Visualisation (real-time dashboards ): Real-time dashboards provide an easy way to view what’s going on at any given time. 
  

• Reporting: Reports can be automated and sent to respective stakeholders at your determined frequency. 
  

• Process & access controls: Data remains safe and secure. You can establish access controls and monitor who sees what information. Processes can be automated to optimise workflows and remove the possibility of bottlenecks. 
  

• Audit trails: Everything that happens in the system comes with a matching record. Every edit gets recorded, too, so audit trails are easy to pull and share. Say goodbye to compliance risk. 
  

There are many case studies out there to help you see how automation tools can provide you with actionable data insights in no time!