Your supply chain analytics go a long way toward optimizing your company’s global supply chain. Still, you need a sophisticated digital model to tap the correct data from Internet of Things (IoT) sensors, the Internet, retail and e-commerce register receipts and the growing Metaverse. With this analytical model constructed, you can leverage a proactive approach using predictive analytics.
Analyzing your supply chain can help streamline processes and simplify acquisitions, but it also helps identify and eliminate waste, manages cashflow and uncovers risk patterns.
One of the things I enjoy about our work in analytics is the variety of business problems we solve. While the specifics of the problem vary, our overall objective is always to derive value from the data. Putting the client’s needs first means that we adjust our approach to best fit the situation rather than fixate on a specific tool or pre-selected solution. This variety makes the work exciting, but it also creates challenges in staffing the appropriate skills. Over the years, I have come to refer to our solution to this challenge with the phrase “Analytics is a team sport.”
Many businesses rely on data analytics to help them improve customer satisfaction and lower their costs. But when paired with artificial intelligence, or AI, data analytics can further help your business. Here is some information about data analytics, artificial intelligence and how they can work hand-in-hand to benefit your business.
Data analytics are pieces of data that are used by managers, business owners, and marketing managers to help them determine their customer base and how to grow their business. Data analytics can show you who visits your business, who is interested in your product, what price point your product can best sell at, how engaging your advertisements are and who your target customer should be.
Artificial intelligence takes your data analytics and kicks it up a notch. Much of your data is achieved through actual testing. For example, if your target market is females aged 18 to 25, you may have tried to market to those who are younger and older to see what their interest was and failed. This helped you determine that those in this age group are most interested in your services. Artificial intelligence uses predictive behavior to predict that those who were older or younger wouldn’t have been most interested in your product. Ultimately, this predictive behavior helps the trial and error that goes into the pricey and time-consuming testing that goes along with data analytics.
Data analytics and artificial intelligence work hand-in-hand because your data analytics are fed into the AI system to give a basis for the predictive behavior that AI is able to determine. Artificial intelligence relies on data analytics to provide a full and accurate assessment for your business.
The biggest benefits associated with using artificial intelligence in data analytics is the cost and time-savings. Artificial intelligence is able to more accurately predict consumer behavior based on your data analytics, helping to ensure that you don’t have to go through the trial and error process of testing new products or defining your target audience. This helps you to save both time and money, ultimately allowing your business to grow faster and more rapidly.
Are you looking to incorporate artificial intelligence in your data analytics in the greater Atlanta, Georgia area? If so, we at Starr & Associates would love to assist you. We understand how to use the tools of business intelligence, analytics, and data mining to improve process efficiency and customer service, while also creating effective strategies for improving the end-customer experience and lowering costs. Contact us today to find out how we can help you.
There’s a reason why businesses are trending towards big data. Data analytics can be used to isolate areas of a business that need to be improved, in addition to paring down to the areas of the business that are performing most successfully. Through an internal audit, a business can fine-tune and streamline its business processes, ultimately using performance metrics to improve its productivity and revenue.
It’s often easier to reduce an organization’s costs than it is to increase its income, but the bottom line is the same — an increase in revenue. If you’re looking for ways to streamline your expenditures and improve your cost savings, it’s time to look at your analytic data.
Your expense sheet holds all of the information you need to identify potential opportunities. Identify your largest suppliers and vendors and begin there. Look for opportunities to:
Visualized, aggregated data gives you valuable insights that you might not be able to see on a spreadsheet. This is the premise behind big data visualization: large-scale patterns may only be visible once data is consolidated, analyzed, and visualized. Using the right software solutions, you can better understand where your organization is spending the bulk of its money. From there, you can look at ways to fine-tune your operations.
A supplier may not just be costing you money in terms of raw materials. Assessing supplier performance is also necessary to determine the full impact of their costs. Are delays making it necessary for your organization to delay products? Have mistakes in the supplier chain required returns or additional administrative processing? Supplier performance impacts efficiency, which can impact the system as a whole.
At the same time, contract compliance must also be enforced. If suppliers are required to deliver product under certain guidelines — and they are not doing so — then they are not performing up to their contract. Issues of compliance must be enforced if negotiations are to be useful.
In addition to making decisions based on current spending, you must also consider future spending. If certain areas of your business are about to grow and expand, then your organization needs to focus on developing out these sectors and reducing costs within them. If areas of your organization are starting to become obsolete, then their cost savings benefits are going to be minimal.
Data analysis is not effective if it isn’t used to affect change. Once your cost savings data has been analyzed, it’s time to make simple, clear, and functional changes to the spending of the departments that it impacts.
If you want to reduce spending in your organization, comprehensive data analysis is the most effective way. Through better data analysis, you can drill down to your organization’s spending habits, discovering inefficiencies and identifying trends. Of course, this also requires the right software and the right business processes. You can find out more through the experts at Starr & Associates.