All You Need to Know About Embedded Analytics

All You Need to Know About Embedded Analytics

November 26, 2020

We had a chat with Qlik VP Head of OEM APAC Jeremy Sim to unpack embedded analytics and how it can be used to turn employees into data-savvy gurus.

By Jeremy Sim

Embedded analytics is fueled by the technology and data that is all around us. It ensures data doesn’t go to waste by integrating analysed data within applications and business workflows, providing insights to users – from customers to employees and organisational decision makers – based on their context and needs. From the recommendation bar on an online shopping site to the spending analysis that banks provide to their customers in a mobile banking app, embedded analytics has become an integral part of our lives.

On the business front, we are also receiving more requests from our customers to embed our analytics technology into their solutions. These businesses want to leverage data in the moment to create meaningful insights, discover new growth opportunities, and offer differentiated services to customers that will allow them to stand out in a crowded marketplace.

Embedded analytics is the foundation for tomorrow’s data analytics platform. For example, it can turn COVID-19 challenges into opportunities. The pandemic has forced businesses to accelerate their digital transformation to adapt to restructured supply chains, remote working measures, and changing consumption habits. Businesses are also starting to embrace data and analytics to forecast and plan their next move in today’s rapidly changing business environment.

For that to happen, tomorrow’s data analytics platform requires analysis to be performed with the flexibility to meet any use case anywhere and everywhere. To optimise processes, drive innovation, and increase user experiences, analytics is no longer desk-bound (or dashboard-bound) and must be available via different channels such as external portals, business applications, public websites, and even within software products.

This is where embedded analytics comes into play.

During the pandemic, we have seen our customers turn to embedded analytics to transform their businesses. The Australian Department of Education, Skills and Employment, for example, released an employment programme, Jobs Hub, to connect Australians who have been stood down due to COVID-19 with jobs available across the country. Built on the Qlik Analytics Platform, Jobs Hub was developed using over 3,000 data sources, and Australians can use the platform to search for jobs by location and role.

In addition to collating information on current employment opportunities, the platform also leverages embedded analytics to provide information on current trends in the labour market and give insight into jobs that are in demand. This information has recently been made available to the public through an interactive dashboard providing key labour market statistics and unemployment rate maps at the national, state/territory, and regional levels.

We also have customers like Australian insurance and care services provider, iCare, which uses Qlik’s embedded analytics to draw on worker claims, injury, and insurance data to form actionable insights that can help businesses better understand common safety risks associated with their industry and identify ways to create safer workplaces.

Embedded analytics can also turn employees into data gurus without straining the IT team too. Often, only select employees have access to specific data and have to go through centralised resources – like the IT team – for analysis and insight.

Embedded analytics creates a data environment that sparks inspiration by bringing insights directly to end-users and decision-makers. By embedding analytics at the heart of your organisation, employees can get the answers to questions they may have not thought to ask yet.

Thankfully, the benefit of embedded analytics also lies with how it complements the standard technology that users are already familiar with. With Qlik’s technology, users can gain access to governed data and perform analyses based on their skill sets. We have also embedded our patented associative engine technology into our customer relationship management and enterprise resource planning solutions to help organisations deliver a competitive advantage and accelerate their business value.

But for this approach to succeed, organisations also need to embrace data literacy and be data driven. It’s one thing to make data available and it’s another to truly understand what the data is telling you. The ability for individuals to read, work with, analyse and argue with data must be consistent throughout the organisation. Data literacy – learning it on your own or through company programmes – is important.

If you’re thinking of embarking on your own embedded analytics journey, here are five key questions you need to consider:

Firstly, define your parameters. This is where companies have to identify what is the best way to deliver analytic content to their users and think about how an embedded analytics initiative will affect stakeholders, existing applications, and interfaces. All these answers will then guide you to the right embedded analytics solution that best suits your organisations’ needs.

Second, consider your technical and business needs. This means evaluating analytics platforms based on the depth and breadth of features, scalability, extensibility as well as the total cost of ownership and vendor expertise.

Third, choose an embedded analytics platform. Some factors to consider include the ease of setting up and using it, the platform architecture, and whether it meets the stakeholders’ requirements.

Fourth, plan the deployment of your solutions. Ensure that embedded analytics is introduced in tightly controlled increments. Most companies that use embedded analytics have learned that mistakes will occur in analytical output and that those mistakes can be costly in terms of poor decisions based on bad assumptions, leading to a loss of confidence in the data.

Lastly, build a data literate culture. All employees should have access to governed data and the skill sets to analyse. This will allow them to answer questions, make more informed decisions, and act faster.

Leadership teams need to take a leap of faith, to trust the results from the analysis, and move away from traditional gut feel to become data driven.

Not all organisations use or should use the same embedded analytics strategy. Some organisations build their analytics platform from the ground up, while others invest in pre-built platforms. The journey depends on each organisation’s business and customer priorities – and what analytics approach makes the most sense at the point in time when embarking on the journey.

There is a vast amount of data coming from multiple sources, so a lot can go wrong if there are no strong data management and governance policies in place. You can expect consequences like entry errors, data breaches, and even lost time, revenue, and employee morale.

Businesses need to ensure that they use the right data to generate insights. This involves identifying data errors quickly and resolving those errors to help maintain the organisation’s confidence in data and the insights generated. Additionally, only authorised personnel should have access to the mission-critical data needed for their role. These will come with proper data governance.

None of these are things can be achieved overnight. It helps if you have an agile data analytics platform that can report and enforce them. Still, such systems require finetuning and employee education – ultimately pointing back to the importance of having a data literate workforce.

Employees fluent in the language of data will be able to derive more value from the data they work with and find it easier to understand and adhere to the data governance process. On top of the added benefits of embedded analytics and well-governed data, a data literate company may be able to unlock up to USD 320-USD 534 million in additional enterprise value.

(Ed. Featured image by Photographer ThisIsEngineering.)

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