Analytics: The Key to Driving Success Beyond COVID-19

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In Navigating Change in Crisis, we explore how individuals and companies are adapting to a “new normal.” Learn how organizations, dev teams, and frontline users are adjusting to meet these challenges of our radically altered world.

The global pandemic has driven home the fact that data is vital to the success of every organization. Companies across Australia and New Zealand (ANZ) are realizing the importance of scaling and growing their analytics capabilities — something that has only become even more important in the COVID era.

Sisense recently surveyed over 460 companies across Australia and New Zealand to dig into their data and analytics usage and future plans. The results reinforce how critical analytics are to businesses in the region, both to succeed in the current environment and to grow in the future.

Dr. Alex Antic, voted as one of the top 10 analytics leaders in Australia by IAPA, and Sisense VP and GM of Cloud data Teams, Scott Castle, recently discussed these findings, diving deep into how COVID presents countless challenges but also fresh opportunities for data analytics professionals. 

Who is leading the way?

The COVID-19 pandemic has wrought an epochal change on every kind of business.  Suddenly every business (still in operation) has had to manage a new dynamic.

The first department to be affected by this change is marketing, as marketers ramp up their efforts to reach their company’s remaining customers. Today more than ever, it’s critical that marketers figure out what messaging is landing, and they’ve found that the most effective way to do this is through the use of data and analytics.

This is borne out by Sisense’s ANZ State of BI & Analytics Report 2020 Special COVID-19 Edition, which found 67% of respondents view BI and analytics programs as more or much more important to business operations now than before the pandemic, and marketing is leading the data and BI charge, with more than 50% of organizations reporting the marketing department is currently performing analytics or employing BI solutions.

Dr. Antic reports this doesn’t surprise him, as marketing is one of the original data-driven businesses in most organizations as it’s based on return on investment.

“Marketing needs quantitative metrics to justify every dollar they’re spending, the return they’re getting, and the revenue generated, so it’s one of the best examples of why you need a data-driven, evidence-based decision making culture within an organization,” he explains.

“For me it’s natural to see the uptake and the proficiency of some marketing departments in using analytics. You just need to look at some of the world’s leaders in advertising and marketing, like Facebook, who are pioneering how they target their customers using leading edge technology, and the wealth and abundance of data at our disposal these days, to see the true power of analytics in marketing.”

There are also clear benefits of departments beyond marketing, in particular HR, finance, and operations, to use data and analytics to drive their strategic visions and drive business.

Scott says COVID has prompted many business departments to ask themselves if they are undertaking reporting, data and analytics in the most efficient way.

“They’re now being asked to project and predict the future, and to analyse more sources of data together to give a more holistic picture than they’re accustomed to. And so I’m seeing a shift in not just the amount of data analysis going on but also the quality of the kind of questions that are being asked, as the market has changed,” he says.

The region has embraced the use of data and analytics to realize strategic value this year, and is leveraging analytics and AI to provide support and targeted customer value to their audience, and this will continue post-COVID.

BI & Analytics Report for ANZ 2020

Data analytics — the competitive edge

One of the issues regularly surfaced organization-wide is that the data analysis built for some businesses may not be suited to the kind of work necessary in the current environment. This is particularly relevant when looking for new opportunities and new growth, which requires looking at optimizations not needed in the past. 

Scott explains this is both a challenge and an opportunity. “The opportunity is absolutely everybody has been affected by this change, and everyone’s struggling with the same thing. So if you can be one of the few companies in your segment who really can master the data you have to make smart decisions, you have a vastly improved chance to suddenly shift to a market leadership position than you would have had in a stable environment.”

Now is a perfect time for data to help lead the charge in changing the dynamics and bringing new companies to the forefront because of founders’ ability to execute more effectively than competitors.

Sisense’s survey found many businesses are now excited and optimistic about data usage and insights, and what it means for business success moving forward. Data professionals within the ANZ region are optimistic about business stability despite the pandemic, with 47% looking to stay afloat over the next six months and nearly a third (29%) are looking to scale and grow. Only 22% are cutting back over the next six months. 

Data maturity challenges and opportunities

Data maturity and C-Suite buy-in around analytics has increased, however, there is still a sense of untapped potential to increase data analytics capability in the region. 

COVID has played a part, as many organizations had to pivot and respond quickly, building up their analytics programs and awareness of gaps and how to address them.

Some challenges still remain, however, such as underdeveloped data capabilities, the ability to clearly articulate a business problem, and then measure the data/technical solution in a quantifiable way.

Dr. Antic explains some businesses don’t know how to develop a clearly articulated business problem in order to resolve it.

“They want to solve some complex problems that they can’t articulate or understand, and they have this unrealistic notion that data and analytics can easily solve some vague, ill-defined business problem, which is the wrong way to go about it,” he says.

More mature organizations and senior analytics professionals have the ability to develop a clear understanding of what the problem is, what problems are viable to be solved by analytics, and come up with technical solutions that are measurable and have some quantitative basis.  

The changing role of the data professional

Budgetary constraints, skills challenges, education around data, and the best use of employees’ time, remain key challenges locally and need to be solved. As Scott explains, there is also the risk of data scientists being seen as the solvers of all business problems, and they become overloaded with irrelevant questions.

“I’m seeing the data analyst, and the data analytics teams, suddenly becoming the perceived source of all business decisions, and the CEO, the CTO, the CFO are just hammering them with questions,” he explains. “There are a few questions that are really important and require a good analyst or data scientist to help solve. There’s also a bunch of questions which can be solved by the questioner going back into the BI tool and pulling up their own chart. 

“This skill is a limited resource, so companies have to start thinking about how to prioritize and send the right questions, the most impactful and the hardest question, to the data team.” 

It’s important to match the right contributor to the right type of question and not just throw data scientists into a lot of basic reporting, Scott says. Companies should also not use data analysts to try to solve massive predictive problems or use either one of them to solve low-level tasks like routine group and count, he adds.

“Understanding the role of data for business success is key moving forward,” Scott says. “The right BI and analytics tool can make a good difference, however business must also consider adequate resourcing and and skills to best utilize these tools.”

Scott also highlights how there’s pressure to try and get all data into the same format, and to attack it with one tool. 

“And I think there are two challenges in this: One is just the technical challenge, not every question is answered with one particular tool, there’s no one analytics that will always work. Businesses need a whole tool chain that changes based on the question you’re asking,” he explains.

“The other challenge is an over standardization of the data culture and the people. When you teach a single methodology for analysing data, for approaching questions and getting access to the answers, and what kind of answers you’re looking for, you end up with single results. The more you over-standardize, the more you force every answer to look the same. It’s when you have unusual approaches, or two or three approaches to the same question, which allows you to really have confidence in the data and you don’t get that with over standardization.”

Key tips to improve your data capability from Dr. Alex Antic

  1. People and culture. There are a number of facets which are key to successful data and analytics, and they’re all very much related to people. Having the right people in the organization in the right roles and frequencies to be analysts, data scientists, and software engineers to enable capabilities from a technical viewpoint is vital. 
  2. Strong technical leader. A strong technical leader, who understands the solutions and can guide the team is also key. This leader needs to be adept at finding the right problem to solve and able to work closely with people as an evangelist and trusted advisor within the organization. 
  3. Democratization of data. Democratization of data within the organization is vital. This process supports education (such as improving data literacy) and helps create and support the data strategy for the organization so that the C-suite has a clear understanding of how to use data. This all contributes to a culture of innovation, experimentation, and exploration. It’s vital to collaborate, share data, and knowledge throughout the organization.  
  4. Right tools/open source. It’s important to have a suite of tools, an open source framework, as well as any vendor-specific tools, in order to not over-standardize. This also gives analysts scope to be able to use the tools they prefer depending on the problem at hand. 
  5. Ethical use of data/privacy. It’s becoming much more important for organizations to be able to understand ‘responsible use of AI’, how to deal with bias, and the ethical concerns around fairness in data, as well as how it will be used by the end user.  
  6. Communication. Communication brings all these elements together. Communicating the benefits of a strong analytics program empowers you to build up a winning coalition, so people, analysts, and business leaders can understand and embrace the benefits of analytics internally.  

How many of these best practices can you start putting into play at your organization? Even two or three can go a long way towards helping you get more from your company’s data — a must-have if you’re going to survive in the coming business environment.

The Leveraging Analytics in ANZ to Drive Success Beyond COVID-19 webinar is now available to watch on demand.

Leveraging Analytics in ANZ

David Huynh is a customer success manager with Sisense. He holds a degree in Business Information Systems and has spent the last 9 years in a variety of fields including sales and project management. David is passionate about helping businesses leverage data and technology to succeed. When not in the office, he enjoys cooking, traveling, and working on cars.

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