Automating intelligent analytics is a great way to streamline business processes and drive more effective results. However, it requires a full buy-in from executives and employees.
Data analytics automation is a process that automatically gathers, prepares, and analyzes large amounts of data. It can also create reports and make recommendations based on user preferences.
1. Streamlined Processes
There are a variety of benefits to streamlining your business processes. This includes reducing costs, improving employee productivity, enhancing customer satisfaction, and building resilience. It also allows for more consistent and streamlined communication across the organization, which helps employees get their work done more efficiently.
Streamlining can also improve the accuracy of documentation. This means that you can easily troubleshoot future risks and make more informed decisions.
It can also reduce the time that employees spend on tasks that don’t directly contribute to their goals. For example, if your accounts team spends hours a month performing a dated process that can be automated, this can result in reduced operational costs and more time for them to focus on other aspects of their job.
When implementing streamlining, it’s important to thoroughly dissect the process from top to bottom. This can include mapping out the process visually and ironing out any redundancies or inefficient steps.
Next, it’s important to determine the cost associated with each process so that you can prioritize which ones should be streamlined first. This could include staff time, supplies, and technology costs.
In addition, it’s critical to understand which employees should be involved in the process improvement. Having them involved in this process will help you earn their buy-in, which is key to success.
Automating intelligent analytics is a smart move for any company looking to drive business success. It can help you to increase efficiency, cut costs, and improve customer satisfaction, while also building a strong business resiliency and creating capacity for continuous transformation. It can also help you to improve decision making and reduce errors, which will benefit your organization in the long run.
2. Faster Insights
As more and more businesses rely on analytics to drive business success, they will need to incorporate automation of intelligent analytics into their processes. This will help them obtain faster insights, thereby driving better business results and making their organizations more profitable.
Faster Insights
Data-driven intelligent automation enables businesses to gain fast, comprehensive and actionable insights from cloud-scale data. It also enables businesses to quickly identify and mitigate risks, improve customer journeys and optimize operations.
In addition, this type of BI technology can be used to help people with various analytical skills gain access to the insights they need, regardless of their level of knowledge. This will promote data literacy and make the entire workforce more capable of gaining insights and acting on them.
This is done by automating tasks like data preparation, data analysis and visualization, as well as recommending associations between different sources of data. This helps users focus on the most relevant data, and eliminates repetitive and time-consuming tasks.
It can also proactively detect changes in the data to inform users about what, when and where these change occurred so they can take action immediately. This is particularly useful in dashboards where users can see a real-time view of what is happening with their data.
Some BI vendors have already implemented augmented analytics within their products to address the need for faster, more relevant insights. For example, Yellowfin implements guided NLQ (natural language query) and Assisted Insights (AI and machine learning) in their dashboards to allow users to ask questions of the data and get the answer they need instantly. These features can be accessed directly within a dashboard, so no additional setup is required to use them.
3. Better Decisions
Business intelligence (BI) tools help organizations make better decisions by surfacing information and insights that align with current questions. These tools also spot trends at a granular level and help teams understand what they may have missed.
These insights can help teams prioritize their efforts and focus their energy on areas where they will get the biggest return on investment, such as sales. They can also spot opportunities that businesses aren’t currently utilizing, such as new marketing campaigns or new product offerings.
When companies use intelligent analytics, they can automate processes that have become time-consuming or inefficient, such as analyzing data across multiple systems. Automation helps companies quickly and easily turn data into actionable insights that drive business success.
It can also help a company transform its data culture and mindset. Children’s apparel giant Carter’s, for example, migrated to Tableau and Salesforce, transforming into a data-oriented company with a robust data culture that encourages employees to leverage and analyze their data.
For companies that deal with a lot of data and have a large number of stakeholders, automation of intelligent analytics can be particularly beneficial. The process can radically reduce the amount of time required to prepare and analyze data, freeing up staff to focus on higher-value initiatives.
Decision making is more complex than ever before, and it’s a continuous process that needs to be networked to account for uncertainty and ensure a range of options are being considered. This type of decision-making is referred to as decision intelligence, and it’s a key differentiator for companies that embrace it.
To ensure that businesses are able to take full advantage of these benefits, they need to implement intelligent automation of their decision-making. By doing so, they’ll be able to maximize the value of their existing investments in data and analytics, and enable their business leaders to make informed decisions that lead to a successful outcome.
4. Reduced Costs
Intelligent automation can be a great tool for companies looking to reduce their costs. In fact, a recent Deloitte report found that companies with intelligent automation systems saw cost reductions between 25% and 40%.
A major benefit of automating processes with intelligent analytics is that it enables companies to reclaim time and energy from workers. This leads to improved productivity and enhanced organizational efficiency. This also allows employees to spend more time on projects that matter most to the company and their career goals.
Additionally, companies can use intelligent automation to augment employee decision making by providing them with critical insights into their data patterns through process mining and other data analysis tools. This helps to lead to increased job satisfaction and ultimately benefits the company as a whole.
Businesses also often see significant savings by automating processes that are prone to human error. This decreases exceptions and ensures processes run successfully and accurately, resulting in higher customer satisfaction and a more positive brand image.
For example, if a company automates the cataloging of raw materials, it can save PS5 million in annual costs by avoiding the need for human labor to update and track commodity prices. This saves the company money by allowing it to focus on negotiating better prices for raw materials.
Another benefit of automated processes is that they can increase customer satisfaction by enabling them to communicate more effectively and get answers more quickly. This can be accomplished by integrating chatbots or other intelligent bots into the customer support process to answer questions and address concerns.
Finally, intelligent automation can help to shift human capital costs by implementing RPA or IPA to replace some full-time employees with software robots capable of handling their duties. This enables companies to free up staff to focus on projects that demand their creative and judgmental skills.
5. Scalability
Scalable analytics is a key component of a business intelligence (BI) system. It can handle growing data volumes, users and costs while maintaining optimal performance.
This type of analytics technology can be applied to all areas of a company, from the back office to field operations and customers. It can help boost customer engagement, analyze operational metrics, and document business processes.
A scalable solution can also make it easy to share insights with everyone in an organization, including managers and executives. This makes it easier to drive user adoption and increase self-service activities.
According to Techopedia, scalability is the ability of a product or system to function well with a larger size in volume. This can be measured in terms of users, storage capacity or the maximum number of transactions handled.
In software systems, scalability can go upward or downward; a product with scalability going up means it can add more users and handle larger amounts of storage without reducing efficiency. It can be difficult to scale a program down because it may require refactoring the code or changing storage options.
Likewise, a network that is scalable is capable of adding new computers and servers to expand throughput or boost security without affecting the overall system. This can be accomplished through clustering, parallel processing and automatic load balancing.
This is important for businesses that are expanding rapidly and need to increase user volumes and reduce costs. Additionally, a scalable platform can help ensure that the software remains available to those who need it, even as the company grows.
