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Stop stalling – use data to accelerate big decisions
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Key takeaways
- The ability to accelerate decision-making processes is within closer reach than ever before.
- While Australian businesses recognise the need for speed, few are taking meaningful action.
- Globally, new technologies such as machine learning and AI could become crucial to decision making.
The internet’s early description as an ‘information superhighway’ was accurate in more ways than one. As well as bringing the world’s globally sourced data to our fingertips, it upended expectations around the speed in which processes are completed.
This behavioural change only accelerated as digital technology continued to evolve. The arrival of smartphones cemented our expectations for new information and experiences to be delivered in the blink of an eye, whether looking up an address, streaming music or videos, or connecting with others through instant messaging. It’s even possible to price match or switch your home loan in minutes from a handheld device.
Although these new behaviours have been crystalised in the consumer space, a different scenario exists for businesses. On the technology side, new breakthroughs in data analytics, machine learning and artificial intelligence have unlocked the ability to quickly decode large stores of information. This, in turn, can fast track crucial decision-making processes, potentially giving organisations a competitive edge.
So why haven’t businesses become as data enabled as decisions in our personal lives?
As I recently argued in PwC’s report Big Decisions: Let the data do the talking, these new opportunities are not yet being fully seized. In a quest for more speed, many Australian businesses may be stalling.
The need for speed
Accelerated data-informed decision making can come in many shapes and sizes, depending on the industry’s particular imperatives or needs. In manufacturing, for example, data can play a crucial role in the decision to develop and launch a new product before a competitor, or scaling back operations before they become too costly.
In the mining sector, where the product is fixed and the market operates on long-term cycles, swift data-informed decision making can play a role in risk management. A mining company drilling in an open-cut coal mine could equip its drills with sensors, providing real-time data into the temperature of the drill, its speed of rotation and the composition of the ore being drilled into.
Using this data, the mining company could be alerted almost instantly if the composition of the ore changes unexpectedly. This allows it to make faster operational decisions, such as replacing the equipment or adjusting the drilling operation, saving time, money and mitigating risks before they arise. Who wouldn’t think that’s a smart idea?
Creating an agile workflow
Data-led decision making sets the stage for company structures and workflows that are optimised for agility, providing the capacity to capitalise on opportunities as they unfold.
This compares to the status quo, where companies can mull over data for days (or even weeks) at a time before taking action. The result is a brittle workflow where trends and obstacles are identified more slowly, crucial decisions are delayed and any necessary pivots or adjustments are all the more difficult.
The importance of speed in decision making, and the role new digital technologies can play in accelerating this process, has not gone unnoticed by Australian businesses. The Big Decisions report found ‘speed to insight’ ranked high on many leaders’ lists of priorities, and was a key motivator for adopting analytics technology over the next five years.
While the road to faster decision making is clearly paved by good intentions, the current state of analytics adoption trails behind global peers. According to the report, only 20% of Australian businesses were using analytics to identify new opportunities. Of these, 5% were actually acting on data-driven insights – less than half the 13% global figure.
Some of the organisations I visit can spend months procrastinating in committees, with poor decision-supporting evidence. They are often still debating how to fund their data analytics programs, or they’re trying to make it an agenda item for the next executive or board meeting. In 2016, this is somewhat astonishing.
Mind versus machine
For the vast majority of Australian businesses that have yet to embrace analytics, the next few years will be crucial. New digital technologies, such as machine learning and artificial intelligence, will continue to become more accessible globally.
Like data analytics, these new technologies are expected to enhance the decision-making process. Machine learning, for instance, can empower executives to visualise different complex business scenarios more effectively, pairing these insights with human judgement to accelerate the speed of decision making.
Companies combining machine learning and human judgement in a decision-making context includes Dataminr, which analyses social media data to immediately alert clients about relevant events. For companies where time is of the essence, such as stock traders or news organisations, this up-to-the-second intelligence (a little-known regional news organisation could tweet a breaking story about a listed company, for example) can provide crucial lead times over competitors.
Another company, Clarifai, uses machine learning to visually recognise objects appearing in video, doing so much faster than the time it takes to watch the video itself. Using this technology, advertisers can match advertisements to video content more efficiently, automating a previously labour-intensive task in the advertising and media industries.
Gearing up to go fast
The integration of machine learning and AI will take time to be completed at the global level. PwC’s Global Data and Analytics Survey 2016 revealed that 35% of global CEOs currently rely on internal data and analytics, while 33% draw from experience and intuition and 25% use external advice. Machine learning and AI will likely alter these ratios, augmenting human judgement and experience to make the decision-making process quicker, more accurate and cheaper.
There’s no denying that speed to insight, along with accuracy and agility, can empower companies to make better decisions. That’s why it’s important to start experimenting with new technologies and use cases now, preparing business leaders to put their best foot forward in the race to make crucial decisions in a timely manner.
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