It can sometimes take time to understand the role of data in business, particularly for those not privy to its power for decision-makers and business leaders. Enterprise has evolved beyond the simple cardboard business card and cold calls – data leads the way in driving operational success. As a result, in the twenty-first century, analytics has become mainstream, and qualifications such as a business analytics graduate certificate are now empowering entrepreneurs to use data to make informed business decisions.
What does this shift to data-driven decision-making mean for business? For many, the rivers of data flowing into a company vary – from sales to marketing, and everything in between, data is driving a veritable renaissance in business operations – managers, wielding the right data, can make decisions that can drive success. If given short shrift, however, poor application of analytics can destroy a business – just ask Blockbuster.
Data-Driven Decision Making – A Competitive Edge
Data is everywhere. From the GPS data that your phone stores, to the transactions on your loyalty cards, it’s estimated that globally, more than 300 million terabytes of data was generated today. Understanding a small proportion of the data that runs through your firm can be immensely important – take, for example, the sales that a shoe store might make during the back-to-school season. Understanding what brands sold well, and what underperformed, can inform sales managers on the brands that the customer base would prefer to buy.
Woolworths, Australia’s largest supermarket chain by store size, exemplifies this. Understanding that every store is different, Woolworths is empowering staff to shop for the data they need, allowing staff the flexibility to dive in and investigate datasets at their discretion. This level of flexibility provides the opportunity for sales teams to use data to gain a competitive advantage for their business – with more than 35% market share in the Australian grocery space, enabling data teams to succeed is crucial.
The Strategic Importance of Quality Data
To drive success in analytics, data must be of a high standard. Poor data quality can impact a business significantly – hampering the ability of data users to make informed decisions. It can also make decision-making using data extremely difficult, particularly if the veracity of a dataset is brought into question.
To build a strong analytics base, strong data standards must be developed, and enforced at an enterprise level. This can be done by applying three core standards – using well-defined data collection methods, ensuring that an effective data management strategy is in place, and finally, having well-defined data governance policies in place, to ensure that decision-makers are using relevant, up-to-date data. Additionally, data that is no longer relevant must be stored or destroyed in a way such that it does not present a significant risk to a company in the future.
Quality data goes hand in hand with quality analytics. Poor quality analytics, in turn, can cause immense financial pain for business – such as the $500 million disaster at US real-estate marketplace Zillow.
Analytics Can Supercharge Success
Data analytics can be a challenging field to master. However, if a company can master it, the use of high-quality analytics has the potential to drive profits at a rate that surpasses competitors.
Analytics can have many operational benefits that go beyond the bottom line, however. National post provider Australia Post exemplifies this, with a data analytics strategy that looks at the capacity of data to identify potential safety and handling issues while working with operations teams to introduce changes that mitigate the number of injuries that happen within the Australia Post workforce.
For business-to-business operations, being able to share critical insights can be a powerful way to demonstrate how a product or service is helping business. Loyalty provider Flybuys, for example, created a data-sharing platform that allowed rewards partners to tap into the wealth of data that Flybuys receives. This level of near real-time decision-making allowed Flybuys to set itself apart from competing loyalty services such as Qantas’ Frequent Flyer program and enables rewards providers to use high-quality data to drive their decision-making.
Quality data analytics is not only beneficial to your team – it’s advantageous for customers, who can be targeted with relevant, quality campaigns. It’s particularly useful for stockists and sales teams, who can use insights to make informed decisions and be data leaders in highly competitive industries.
The Future is Data
The days of using pen and paper to track customer sales are almost well behind us. The digital receipt is now the norm – and with that, many changes have impacted the realm of information. Data has transformed nearly every facet of how business stakeholders use the details to make informed decisions, from the safety focus of Australia Post to the sales knowledge of Flybuys.
The role of analytics in enterprise data maturity is bright. It’s evident that as we race towards this new realm of data-driven decision-making, the ability of high-quality data analysts will not be underestimated. Will your business be well-placed to handle the data challenges and complexities that lie ahead? Only time will tell.
