This unique climate has also revealed the importance of predictive analytics as being critical in helping businesses anticipate disruption and identify new markets. By blending historical or first-party data with external signals and third-party data, businesses can better predict trends and plan for more accurate scenarios. Predictive analytics and intelligence capabilities are revolutionising the way businesses operate and supercharging the ability for business to plan in a connected way.
Taking data use to the next level through predictive analytics is a non-negotiable for businesses in 2022. It will be the superpower in the c-suite tool kit during unprecedented times. But to do so, businesses need to start with upskilling their team, ensuring the company culture is ready and maintaining good quality accurate data sets.
Data centric company culture
In many cases, businesses are sitting on mountains of data not being used to its full potential. Beyond having the right data analytics tools in place, having the right talent is a crucial puzzle piece in unlocking this data. Businesses should be investing in upskilling tech teams to be well versed in AI-driven analytics. As we gear up for 2022, which is likely to continue to be volatile and unpredictable, having these skills in a businesses’ arsenal will be crucial. Being data-savvy does not just extend to the IT team, it is also the role of the wider organisation and leadership team, especially in light of the job shortages facing Australia. This means ensuring your company has a ‘data centric’ culture where employees feel confident in using data to inform decisions will be critical.
High quality data
In addition to the right skills, businesses will need access to high quality data. Part of achieving this means fostering a company culture that does not limit access and sharing of data across the organisation. Understanding what data lives in silos in different departments in the organisation is a crucial first step in predictive analytics. Being able to blend this internal data – what you know – with third-party signals – what you don’t know – will not only help you uncover new opportunities for growth, but will give you a more accurate and holistic view of the future of the business so you can make more strategic decisions.
Leveraging third-party data and insights is particularly important in today’s dynamic environment where consumer behaviours are shifting at a rapid clip and unprecedented events from floods and fires to a global pandemic can make even the most well-thought-out plans irrelevant in a matter of minutes. Just think about the impact predictive analytics could have for a supply chain leader today as they navigate volatility across their network – from sourcing to logistics. With predictive analytics, supply chain leaders can digitally model their entire network and then leverage external signals – like weather data and consumer trends – to predict potential points of failure, forecast more accurate demand, and ensure their supply chain is agile enough to pivot if and when unplanned disruption occurs.
From mitigating the risk of fraud to identifying new market opportunities, predictive analysis has so many use cases. For businesses in 2022, predictive analytics will supercharge planning. Today, planning often sits in separate parts of the organisation and acts as a box tick item at the start of every year or quarter where businesses leverage historical company data to make best guess estimates about the future. With predictive analytics, businesses will be able to pull data from HR, sales, finance, and supply chain software to one centralised place, then marry that data with third-party data and external signals – like weather data, consumer trends, etc. – to predict potential outcomes and better anticipate points of failure within their operations. This will equip businesses with a more accurate view of the future, and will ensure they are prepared to make quick, informed decisions with confidence as needed.
Predictive analytics is revolutionising the way businesses and government bodies operate. For example, recently, an Australian telco organisation has been using predictive forecasting and continuous, agile scenario modelling to help better understand customer incidents. The advanced AI and machine learning capabilities have allowed them to understand the network incidents by customer demographic, improved its forecasting of network incidents and assured remediation work based on seasonal weather patterns to offer faster maintenance.
Another great example of predictive analytics in action is with US based cybersecurity organisation, Extrahop. The company was exclusively targeting large enterprises, but sensed that there was a big opportunity in the mid-market and wanted to expand their go-to-market strategy. To get a sense of the opportunity, Extrahop took internal data and augmented that information with AI-enriched, third-party data to give them a more actionable, holistic view of their total addressable market. This gave them the confidence to go after a new market resulting in a 3.8x larger average deal size across segments.
Data has been the top item on the business agenda list for years now but as we move into 2022 the real challenge for businesses will be moving beyond historical data and harnessing external data sources to drive more predictive planning and decision making. In fact, the predictive analytics market size is set to grow to US$21.5 billion by 2025, at a compounded annual growth rate of 24.5%. With businesses still facing so much uncertainty, making informed decisions by combining company data with external insights and signals will be the golden ticket in 2022.