Datahut Blogs (9 Part Series)
Data is ubiquitous. This tremendous amount of information can change the way your business works and the way consumers view it. But to leverage datasets, you need to select the appropriate tool for big data analytics. These tools can then help you in data-driven decision making. It is essentially the foolproof way used by data masters to transform businesses.
What is Data-Driven Decision Making?
There is an enormous amount of data around you. How judiciously you use this data can determine which course your business will take. You can undoubtedly discover a pattern or correlation from a dataset. With the right data analytics tools, you can uncover these insights and hidden information. This process is known as Data-Driven Decision Making. With DDDM, you can work wonders for your business.
Steps to follow in Data-Driven decision making
Now that we have understood DDDM, it is time we know how to use data to drive decisions.
STEP 1: DEVISE YOUR STRATEGY
You can find a massive amount of data. It is best that you filter the ones you need. To get your strategy in place, think about what you want to do with your data. For instance, you might want to get new leads or compare prices.
Curate your strategy based on your objective. Staying focused on your goal is very important when it comes to DDDM.
STEP 2: SELECT YOUR KEY AREAS
Each interaction between your customers and executives generates a vast pile of data. Therefore, it is vital that you select the source of data which is most crucial for your strategy. Or else, you might be tossed around in a data trap. For example, to streamline your workforce, you need to take a look at operations data.
STEP 3: PICK THE DATA YOU WANT TO TARGET
Once you have selected the problem you want to address, it is essential to streamline the dataset further. By doing this, you can target the department along with the problem that you are solving. You can do this based on measurable goals or KPIs.
For best results, select data across multiple departments since most strategies rests on the shoulders of multiple departments. This step helps in managing data storage charges. Moreover, more streamlined data gives better results.
STEP 4: ANALYZE THE DATA
You can prepare the best dataset by collecting data from various departments, followed by their filtering. Sources can either be external or internal. Highly variable data will bring each aspect of your business into consideration.
To analyze the data, you need to verify the quality of your data. Generally, you have to choose your data analytics tool depending on your goals and the complexity of the dataset. An excellent data analytics tool can effectively connect data from different sources.
STEP 5: START ACTING ON THE INSIGHTS YOU GAIN
The insights you gain from your data can revolutionize your business. But this depends entirely on how well you present it. Big data technology have some players that can deal with even the most complex datasets very well. Once your insights appear relatable to decision-makers, you can put your strategy into action.
Where can you use data analytics to implement data-driven decision making?
big data analytics applications
1) Brand performance evaluation using data analytics
Businesses have been investing in branding campaigns for quite some time now. But there is a catch. In most cases, they are not aware of how effectively their campaigns are enhancing their brand’s performance.
“You can’t manage what you can’t measure.”
Here, these lines said by Peter Ducker help in clearing the smoke. The need of the hour is big data analytics. You need to identify the specific issues with your business and the department it pertains. A “top-down approach” can quickly help you put your finger on these issues.
Studying data from multiple sources will aid in data-driven decision making. An ideal dashboard for your business should work as per fundamental matrices of your choice. This dashboard should then be able to give a clear picture of your brand’s performance as compared to your competitor’s.
Most businesses invest in brands to work on certain crucial factors. These factors are equity, loyalty, attitudinal, penetration and sales, namely. The main focus for data science masters is to integrate these factors and bring actionable insights to the table. These insights can pertain to different geographies, consumers and products.
From a business point of view, big data works best when you perform analysis over a period. Subsequently, all these actions will reflect on the ROI of your business.
2) Risk management through data analytics
The contemporary marketplace has remarkable connectivity. But this connectivity increases susceptibility to a whole range of risks related to fraud and operations.
You can leverage big data analytics can to establish tight control over the marketplace. Here, data forms the basis on which you can design predictive models. These models can consequently help you in monitoring and analyzing user behaviour. With ample knowledge and prediction, these models can help you in preventing frauds.
Data analytics can help you understand all facets related to a financial transaction. These data-driven decisions become foolproof once you are aware of potential downsides. In such situations, data science becomes an asset.
Running countless scenarios becomes a time-taking task. But with big data analytics, reactions to these scenarios can be generated in comparatively lesser time. This process eventually leads to better data-driven decision-making.
To make the most out of consumer data in this segment, you should collect and analyze both internal and external data. An integrated analysis paves the way for better decisions.
3) Understand and modify consumer behaviour with data analytics
As a business, your success depends highly on how well you understand your consumer’s behaviour. Insights from customers directly help you in improving your products or services along with enhancing the consumer experience.
By properly segmenting your buyers, you can make various deductions about your consumers. You can understand their needs and responses. Then big data analytics can be used to understand their habits and preferences.
For instance, predictive analytical models can help you measure the effectiveness of marketing campaigns. This understanding will help you in improving your campaigns.
Furthermore, consumer behaviour can aid in progressive budget allocation. Understanding what motivates your consumers better will bring data-driven decision making into the picture.
For example, data science helps you in learning what influences your customers to buy from you. Having realized this, you can put money in the most-influential campaign and thus optimize your finances.
4) Design your ideal marketing campaign with big data
Marketing has the power to turn the table in favour of your business. By understanding the trends from the past and present, you can plan for a better future of your company. Data analytics can help you understand consumer needs. With this knowledge and data-driven decision making, you can come up with more promising marketing campaigns.
An excellent example of such campaigns designed by data masters are the personalized e-mails you receive. At certain instances, you google a product, and then the same product comes in your feed. These are one of the takeaways of an era driven by data science. All these methods push marketing to a whole new level.
Big Data as the Solution to Problems in the Public Sector
The answer to most of the problems of government agencies or any other public sector company is data analytics. Not only can it save money but also ensure efficiency.
While working on public policies, it is essential to understand the opinions of ordinary people. Thorough data analytics can help tackle the biases about a particular topic. Thus, it will help you in designing more promising government schemes.
This process comes under the immediate scope of data-driven decision making. Afterwards, data masters can also analyze the effectiveness of these policies. Based on the results, you can choose to amend those schemes.
But in the public sector, data analytics comes with its fair share of problems. Agencies working within a tight budget won’t be able to hire promising data scientists. As big data analytics require a broad range of skill-sets, finding experienced employees is also tough.
Also, some issues assigned to public sector agencies are long-term problems. Analyzing and devising predictive models can be challenging in such cases. The enormous amount of data makes this task time-consuming and complicated.
Furthermore, big data analytics can help government agencies in understanding public opinion. This step enhances the communication and decision-making of such agencies.
How Big Data Analytics Can Help Private Companies Win Big
Big data can revolutionize the way businesses work. You can collect data to know about consumer’s interaction and purchasing patterns. You can implement machine learning on these datasets. As a result, you can enhance the user experience, which is a significant reason why businesses flourish these days.
One can leverage data analytics to know about products likely to be purchased by your consumers. You can then provide them with personalized shopping experience and discounts. With various tools in place now, you can easily understand your competitors.
One of these tools is price comparison. It helps you in deciding what price suits best for your product. By pricing your products correctly, you can easily beat the competition. Data about your competitor’s sales can help you in winning over them.
A successful business focuses equally on their internal workflow. With data analytics, you can monitor employee performance. This step will help you in pinpointing areas that need improvement. Here comes the scope of data-driven decision making. DDDM will help you streamline the functioning of departments with the help of well-planned activities.
In another aspect of finances, DDDM will help you focus on security. It can help you manage the finances better along with keeping frauds at bay.
Read the original post here: https://blog.datahut.co/how-data-driven-decision-making-is-driving-businesses-towards-success/