The pandemic has sparked widespread acceptance that data is vital to the success of every organisation.
Companies across Australia and New Zealand (ANZ) are realising the importance of scaling and growing their analytics capabilities — something that has only become even more important as lockdown continues to ease and business activity begins to pick up momentum.
In a recent report, Sisense surveyed 460 Australian and New Zealand data professionals and business executives, across different industries and roles, to uncover the impact of COVID-19 on the day-to-day workflow and business challenges of BI and analytics professionals. The survey found 67% of respondents said BI and analytics programs are more important or much more important to their daily operations today, and 55% of companies are using data sources, analytics and dashboards more often or much more often than before COVID-19.
But while the Business Intelligence industry has long promised a future where every worker can use data to make smarter business decisions, that promise has been out of reach for many companies, until now. That’s because we are now on the cusp of an exciting ‘new generation of BI’ that will finally turn that promise into reality.
Unpacking the first two generations of business intelligence
Firstly, we started with “Gen One” BI - on-premises data and heavy-IT driven reporting projects - which was burdensome for both IT teams and end users. While cumbersome and requiring heavy investments, a few enterprises overcame those hurdles and reaped big benefits, lighting the spark for analytics.
Next, we entered the era of data democratisation and self-service, or “Gen Two” BI, which focused on making data more consumable, easy to use and accessible by putting the power of analytics tools into the hands of business users. Although more organisations adopted Gen Two BI and gave out more licenses than ever, this generation’s fundamental flaw was its focus on dashboards and analytics itself.
We asked business users to also become analysts, to step out of their daily workflows to build or find dashboards to leverage data. The result is that adoption of data analytics continues to be a struggle as data volume and complexity grows, with only 24% of firms claiming to have created a data-driven organisation, an actual decline from prior years!
The third generation of BI: The age of action
It is time for a third generation of BI. Like the iPhone, which built on two generations of cell phones and smartphones and finally put mobile technology into the hands of every consumer, this new generation of BI will take the best of the two previous generations and finally empower every worker to make smart, data-driven decisions.
This will be “Gen Three” BI, and we call it: the Age of Action. Let’s take a look at what this looks like.
A new era of analytics that ‘comes to us’
Business intelligence is built on an old data culture that relies on technical experts. In the early days of reporting, those experts were called IT. As technology evolved and tools became easier, the progression of BI moved to reports and dashboards delivered by new experts—analysts. This made analytics more accessible, but still didn’t make self-service data insights a reality across the business. Here’s why: Instead of using technology to put data in front of people where they already are working, we continue to ask people to leave their business apps and turn to dedicated tools or dashboards for answers.
This process is disruptive and inefficient, and often causes users to write it off completely. Dashboards don’t have built-in analytics processes; they share information but do not provide recommended courses of action at the right moment or in a decision maker’s workflow. Business professionals want exactly that: They want a final answer and recommendations on what to do next. They would rather have data and actionable insights come in easily digestible bites versus needing to dig for answers in dashboards and reports. And the truth is they are digging; dashboards are often too broad to address multiple questions, too difficult to customise, and frankly, have too many insights.
For analytics to advance, we must extend dashboards or deliver personalised intelligence to more decision makers. In fact, Gartner predicts that “dashboards will be replaced with automated, conversational, mobile and dynamically generated insights customised to a user’s needs and delivered to their point of consumption. This shifts the insight knowledge from a handful of data experts to anyone in the organisation.” Now, instead of wasting time jumping from where the data resides (in dashboards) to where work is done, embedded analytics enables users to do both simultaneously: get insights and take action.
Automation and ‘invisible’ analytics
The keyword in Gartner’s prediction above is automation. We cannot talk about moving beyond the dashboard without acknowledging the role that artificial intelligence plays in this next phase of analytics. Advancements in AI means we can now scan entire data warehouses in seconds, answer the toughest analytical questions and track meaningful changes in data in real time. And we can do all this without lifting a finger or calling in experts.
Previous generations of BI gave us technology like data visualisation to make data more understandable, the cloud to enable access from anywhere or any device, and extensible frameworks so we can embed data into other applications. Today, when we combine that technology with AI, we can extract data insights and embed them into our CRM, workplace collaboration apps, custom business apps, etc. Instead of asking users to pause their jobs and dig through dashboards for answers, we can put digestible insights and expert knowledge in the apps they are already using.
In this type of world, technology fades into the background. Business workers are in and out of their apps and barely aware that they’re using analytics at all. They’re simply getting the answers they need, making smarter decisions and moving on to the next task. Taking action based on data becomes seamless, automatic and instinctive for all.
Unlocking better business decision-making
Psychologists estimate that we make an average of 35,000 decisions each day. As consumers, we make many of those decisions with the help of data analytics, even if we don’t realise it. We turn to our smart devices for insights about traffic patterns, exercise goals, financial spending habits, and more. Often, those insights come to us automatically in our apps, and sometimes in advance before we know we need it. As a result, we make better-informed decisions, thanks to personalised data.
This is how decision-making should be in businesses too. Every day, our employees, partners and customers also make decisions that impact the bottom line; why wouldn’t we expect the same level of insight in the workplace? In the Age of Action, insights arising from analytics and AI are no longer a luxury, but a necessity for achieving competitive advantages, whether in employee- or customer-facing apps and workflows.
Many businesses are already taking advantage of this new generation of BI. Take GE for example, which embeds analytics into their scheduling software for more than 150 hospitals, helping them predict no shows and cancellations for MRI and CT scans.
Or Air Canada, which has hundreds of gigabytes of data on safety-related KPIs. They’ve integrated AI and analytics into corporate safety processes for their front-line employees so airplane parts can be flagged and replaced before the part fails.
Or closer to home, Australia financial transactions company Profectus, which infuses data analytics to review hundreds of thousands of invoices and agreements on behalf of its customers, reducing millions of dollars in financial waste and leakage.
This is what business intelligence promised decades ago. It’s businesses of all sizes and types, putting personalised, actionable analytics in the hands of all users where they are. No more heavy IT projects with long turnaround times. No more distracting dashboards or attempts to turn everybody into analysts.
Eventually, “let’s look at the data” will become a phrase of the past. This is because the data will already be where and when business decision-makers want it, in real-time, without them even asking for it. They will have deeper insights and make decisions faster and more accurately then ever before.