In just about every area of life, we are increasingly generating ever-larger volumes of data and one of the most valuable uses businesses are finding for it is helping them to make better decisions.
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This occurs frequently and can occasionally be a manual process for organisations. For instance, spending the time to analyse job candidates’ LinkedIn profiles to aid in recruiting selections or determining the areas where your products are well-liked in order to focus sales resources However, the most fascinating data applications are automated and utilised to address significant issues that organisations are experiencing. For instance, when UPS began rerouting its network of delivery vehicles utilising location data and traffic information together with artificial intelligence (AI), it significantly decreased its energy footprint and saved money on fuel and labour expenses.
Similar to this, online merchants like Amazon forecast what goods people will purchase with increasing levels of accuracy by using past customer purchases. In order to keep consumers hooked on its service, Netflix also learns about its users solely from how they use its service. It discovers what material people appreciate and what turns them off. Without the involvement of any human workers, this occurs automatically!
Making decisions that are most likely to advance your business toward your objectives is a sign of smarter decision-making. Business executives’ experience and intuition have always been the driving factors in decision-making. And regrettably, that’s one of the main causes of the alarming statistic that 90% of startups and small enterprises fail. Experience and intuition are vital, of course, but research shows that organisations are 19 times more likely to be profitable when they base their decisions on facts rather than instinct or experience.
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The Benefits of Data-Driven Decision Making
1. Increasing transparency and accountability
An advantage of the data-driven decision-making strategy is that it makes the company’s operations more transparent and accountable. The goal of the data-driven decision-making strategy is to boost employee engagement and teamwork. Organisations respond to challenges and dangers in this way, which boosts general performance. Making the appropriate decisions on their activities is the result.
Because misconceptions become less frequent, fewer errors are made. Employees are more inclined to offer improvements and modifications when they are fully informed of the situation and their specific responsibilities. All because they are aware of the company’s long-term objectives and current situation.
Organisations can effectively gather data, utilise it for compliance and record-keeping, and hold themselves accountable for good data management with the use of objective data.
2. Continuous improvement
The organisation improves continuously when decisions are made using data. They introduce changes gradually, keep an eye on metrics, and modify further in response to the outcomes. This boosts the organisation’s general productivity and effectiveness.
3. Increases consistency
The use of data in decision-making processes guarantees that the company’s outcomes are consistent. This method assists people in understanding how decisions are made. They may also assess the implications of data collection and analysis and take relevant action. Everyone who participates in data-driven decision management learns the essential skills and thereby improves consistency. This is how employees can see if sales are up or down, or if consumers are satisfied. This keeps the organisation informed while also cultivating loyalty, involvement, and accountability.
4. Cost saving
A company that only uses data will not save money. However, you may utilise the data gathered to discover potential cost-cutting initiatives. Perhaps the majority of the budget is being spent on an unproductive marketing plan. Alternatively, one product generates more profit than the others. Data may be used to assess a product as well as to detect and resolve problems. The stronger the data is leveraged in decision-making, the more agile the organisation. This trait enables a company to outwit the competition and earn income. Companies that use big data have witnessed an increase in earnings of 8-10% and a drop in overall cost of 10%.
5. Flexibility and quick adaptation
Predicting market trends and responding quickly will offer a company a competitive advantage. A business that does market research and produces a viable product is considered an industry leader. Once a company receives and analyses data, it makes decisions. Truly agile organisations are more likely to achieve great financial success than the average business.
6. Feedback for market research
Data-driven decision-making generates feedback that gives insight into what customers like and dislike. It’s how organisations create new goods and services, as well as how they predict trends before they occur. By studying data, companies learn what to expect in the near future and what to adjust to improve performance. In this way, companies maintain a positive relationship with their customers.
How To Use Data To Make Business Decisions
It’s best to start with an action plan before diving into data analysis. It should detail how you will find the right data and understand it in order to make sound business decisions. Examine your objectives and prioritise them. Any decision you make should be guided by your primary company objectives.
1. Define the goal
The first step is to identify business goals in order to understand the company’s primary and subsequent aims. These can be as specific as increasing sales, or as abstract as increasing brand awareness. A predetermined target will aid in the selection of key performance indicators and metrics that will affect data-driven decisions later in the process.
2. Data search and preparation
After defining the goal you need to solve and the solution you want to implement, it’s time to locate and apply the relevant data. Gather and organise all essential information. However, access to quality and trustworthy data can be a significant challenge if your business information is spread across several sources. Begin by preparing data sources with high impact and minimal complexity. You can, for example, prioritise data sources with the largest audience. Don’t waste time gathering and analysing data that will have little bearing on your ultimate decision. Collect only those that are pertinent to your goal.
3. Data review and development plan creation
The next step is to study and analyse the data. It is vital to visualise them to make effective data-driven decisions. Visual representation of ideas boosts the likelihood of influencing the senior management and other employees’ decisions. So, look at the collected data and attempt to spot any patterns or trends
If you can use data to prove that your decisions will have a beneficial influence on business growth, it’s worthwhile to spend the time analysing the data in your CRM, customer service reports, and other methods of storing information about your company’s activities. Also, share it with other staff for more efficient work. Using informative text and interactive visualisations to highlight crucial points might influence audience decisions. This will allow them to make better judgments in their regular employment.
Examples of How Companies Use Analytics
Google is interested in what it terms “people analytics.” Google gathered data from 10,000 performance reviews and linked it to employee retention rates in one of its people analytics efforts, Project Oxygen. The information was then used to determine the general behaviour of competent managers and to construct training programs to improve capabilities.
Burberry
Burberry improves efficiency, revenue, and customer pleasure by leveraging big data and artificial intelligence.
Customers utilise loyalty programs through their mobile applications and those who use such services are also asked to provide data, which is subsequently used to make suggestions for online and physical items. Employees in the physical stores can view a customer’s purchase history, preferences, and social media activity. They may use this information to deliver a more personalised experience and boost sales.
Every item in a Burberry store has a unique RFID tag. And when customers enter the store, the mobile app will communicate directly with them about different products.
Netflix
The service has a lot of data and analytics to understand the viewing habits of international consumers. They use the information to create innovative programming that appeals to people all across the world and to acquire film and television series rights.
Conclusion
In this dynamic climate of data-driven disruption, business leaders must view the world through two lenses at once. Firstly, they have to identify high-risk, high-reward possibilities such as entering new markets and altering existing business structures. Secondly, they must retain their emphasis on incorporating analytics into their fundamental corporate decision-making process. By embedding data analytics into their core strategy, business managers may optimise internal business processes, discover new consumer trends, evaluate and monitor emerging risks, and establish systems for continuous feedback and improvement. Driving analytical transformations will thereby allow businesses to acquire a competitive advantage and remain at the forefront of digital disruption.
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Why Businesses Need Data To Make Better Decisions
