While it is encouraged to listen to your gut and follow your intuition when making life choices, when it comes to business decisions, trusting your gut can prove to be an expensive mistake. To keep the business up and running, managers and leaders need to take various critical decisions. In such cases, only data-driven decision making can take them a long way.
Data-driven decision making (DDDM) is the practice of making sure that a company’s strategic decisions are based on facts and information. When your company makes it a norm, it motivates employees to work together and share key data across all departments. Using data analytics help in better decision making by:
1. Eliminating bias (unconscious or conscious)
As human beings, we can’t help but get influenced by our environment, culture, personal experiences, and lifestyle. Whether we are aware of them or now, our biases can have a big impact on our business decisions. Common examples include stereotypes regarding specific age groups or gender to not be the ideal target audience without having an ample amount of data to back it.
When biased decisions are taken, we may miss out on valuable marketing opportunities that might bring us significant growth in our revenue. Data-driven decision making ensures all our decisions are based on verified data and logic. The possibility of being influenced by our biases (conscious or unconscious) is eliminated.
2. Reducing business risks
Business analytics provides in-depth insights into risk management as well as insights on how to improve the overall management. Understanding risk is a key part of optimizing vital business decisions. When it comes to risk management, business analytics is very helpful. It can help in analyzing the organization’s data, whether it is stored in a database or is available in unstructured sources.
Having an idea about what might happen, business analytics can be used for optimising reactions and averting crises in the best way possible. With the right business analytics tools, banks can get a better picture of who they should give loans to.
This revolves around analyzing the credit score and loyalty rating of the potential customer. It can also be harnessed to know whether some high-risk payments are worth the risk at all. Sans business analytics, many resources of organizations are likely to be wasted on customers who might end up defaulting on payments.
3. Enhancing the overall customer experience (CX)
Businesses of all types from almost all industries now collect customer data from various channels, including social media, e-commerce, and retail. Using data analytics for creating customer profiles, businesses can get an understanding of customer behaviour and use it to offer a more customizing and personalized experience.
A retail business (with online and offline presence) can analyze its sales data and use it for social media campaigns for promoting its online sales for various product categories that customers are interested in. Telecom companies can execute analytical and predictive models for ensuring their customers stay with them for a longer period and assessing the success of their marketing activities.
Using data of this sort can help in creating a holistic foundation on which it becomes possible to execute a rock-solid strategy. Having business analytics tools helps a company with the right data to get an upper hand over competitors.
4. Increasing accountability & transparency
One of the biggest advantages of data-powered decision making is that it always leads to more transparency which subsequently accountability in any organization. Data-drive decision making support and improves cooperation and engagement in the team.
It helps companies deal with threats, mitigate risks, and thus, enhance overall performance. It also encourages and increases employee morale and a data-driven decision-making approach helps the management see the objective of data backups. It also significantly aids in everyday decision making.
Objective data, essentially, help in collecting data and using it for compliance and record keeping. It makes companies accountable for managing their data more properly. As far as transparency is concerned, data-driven decisions make sure every piece of information is prioritized, the goals are solid, and the results are measured accordingly.
5. Mitigating supply chain and operational bottlenecks
Companies can successfully enhance operational efficiency by using data analytics. Collecting and carefully analyzing data regarding supply chain shows where there are delays or bottlenecks in production. It also helps predict whether problems may arise in the future.
Say, for instance, the demand forecast depicts that a specific vendor will not be able to take care of the volume needed for the upcoming holiday season. Having this piece of information, the enterprise can now be prepared well in advance to replace or supplement this vendor to avoid production delays.
Moreover, many businesses struggle in optimizing their supply chain and inventory levels. Data analytics can also be leveraged for determining the optimal supply for enterprise products based on factors, like holidays, secular trends, and seasons.
6. Increasing data security
All businesses are susceptible to data breaches and threats. Companies can use data analytics for diagnosing the root cause behind past data breaches. IT departments can leverage this data to parse, process, and visualize audit logs to determine the origin and course of a cyber attack.
IT teams also utilize various statistical models for preventing future cyber attacks. These attacks usually involve atypical access behaviour, specifically for load-based assaults, like distributed denial-of-service attacks. Companies may set up such moels to operate continuously. They also have monitoring and alerting systems placed on top for detecting and flagging abnormalities so security experts can take action at the earliest.
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