Using cloud solutions opens your workforce to using virtually any Internet-connected device to access and process data. That means everyone gets to use the computing tool with which they feel most comfortable whether it’s the office’s iPads or a Windows computer. Another benefit is your office can purchase exactly the number of licenses it requires, then add to it as it hires office staff.
Organizations across the world are finding themselves with increasingly complex supply chain processes to manage. While in the past most commercial enterprises were local, modern enterprises cannot survive in this way. Many modern businesses are finding themselves having to develop new technologies to manage these strategies — one of which may become the blockchain.
Current supply chains are still using management and logistics processes that were developed a long time ago. These are very streamlined processes that involve a small number of components. But supply chains are operating internationally now; even organizations that only deal in local trade are often sourcing their materials from another country.
This introduces many logistical concerns. Supplies and assets must now change hands a multitude of times, shifting responsibility from one organization to the other. Supplies need to be able to be tracked by multiple vendors and businesses, which can be difficult when they are traveling such tremendous distances. Blockchain technology may be able to help.
Blockchains provide a completely transparent and consolidated transaction sheet, which can comprise a multitude of different transactions and verifies each transaction with all other users of the system. In the blockchain, a transaction can be logged and then immediately propagated throughout the system, carrying with it information about the transaction and verifying that the transaction did take place.
As a consolidated but decentralized system, blockchains provide for superior security as they cannot be controlled by any one individual. Data cannot be lost because this data is held by anyone who uses the blockchain, and consequently suppliers don’t need to worry about issues such as securing and managing their own transactional data.
All transactions can be traced easily back to the original source through blockchain, and each entity in a blockchain can be tracked through multiple transactions. This has opened the door for companies such as diamond companies to track their individual assets throughout the entire supply chain, from initial mining to customer purchasing. Not only does this heighten security and streamline logistics, but it also provides vital data throughout the customer purchase process.
The blockchain is a relatively new and disruptive technology, but it has been around long enough that many companies are now seeing its true value within their organization. Through the blockchain, supply chains can enter into a new generation of scalable, consolidated, and decentralized solutions.
Companies will be able to track extremely complex supply chain management protocols with complete transparency and organizations will be able to work together with transparent and easy to access data. All of this will reduce supply chain overhead and costs and make it easier for companies to thrive. For more information about business intelligence and data analytics, contact the experts at Starr & Associates.
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.
How do executives determine whether company initiatives are effective or not? Executives don’t have the time to regularly comb through lengthy reports. They need important information to be delivered to them in as concise of fashion as possible. This is the role that a dashboard plays. Through a well-designed dashboard, executives can get all of the business analytics data they need.
An executive dashboard must be specific, measurable, actionable, realistic, and time-bound. The statistics displayed should be relevant to the organization’s current goals, displaying both metrics that are over-performing and under-performing. These metrics should be displayed in a timely fashion and should allow executives to drill down to further information that is relevant to them.
At-a-glance, the executive dashboard must give a broad spectrum overview of company initiatives, including everything that needs to be improved upon or modified.
Which metrics should an executive be shown? After all, a company is likely tracking hundreds of them — which are most important? Begin with your organization’s most important metrics, such as its net profits. From there, pare down to the metrics that are underlying that, such as sales and expenses. These underlying metrics are what influences your net profits.
If an organization has current and specific initiatives, such as increasing returning customers or improving upon new sales, these metrics should additionally be tracked. This gives the executive actionable information regarding the company-wide initiatives that are currently on-going, so they can determine whether the company is moving in the correct direction or not.
Few people, even experienced company executives, can glean any information from charts upon charts of numbers. Data visualization makes it easier to analyze large volumes of seemingly complex data all at once. Through data visualization, patterns more easily emerge. Pie charts, for instance, can be compared quite quickly to each other to identify current trends.
The right data analytics dashboard will give you a variety of ways to display information. The more varied the information displayed on the executive dashboard, the easier it will be to compare different metrics and identify changes as they occur. There are many software suites out there built for visualizing complex sets of data.
A modern organization is only as good as its data. There is no way for a business to succeed today without tracking its metrics. Moreover, the metrics on a company dashboard give an executive the information they need to make powerful, well-informed decisions for their company. For more information about the role that information plays in business today, contact the experts at Starr & Associates.
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.
Data-driven cultures are far-reaching. Nearly every industry is currently being disrupted through data analytics, and the field service culture is no exception. Many companies are utilizing a combination of unmanned drones, sensors, and data analysis to make field service more effective and comprehensive. Here’s what you need to know.
What if you could predict when a system would go down? With big data, you can. Big data uses a combination of sensors and historical data to identify environmental conditions that could indicate a breakdown. This data isn’t a replacement for traditional field service techniques, but instead, it’s designed to augment field servicing. Big data can be used to tell field service technicians when there could be a critical problem, as well as to fine-tune the number of times technicians go out and when they go out.
Predictive field service models work hand-in-hand with the Internet of Things. Internet of Things devices are utilized to capture data in the field, and this data is analyzed. Big data isn’t magic — it requires tremendous amounts of data which is then used to view patterns. As an example, a certain heat signature might only occur just before an element breaks. These patterns can then be used to create a risk assessment for individual machines and equipment on the field.
A data-driven culture is a cost-effective, safe culture. Better data means technicians need to be on the field less and are on the field when they are most useful. Not only does this reduce field-related industries, but it also reduces the overall cost to a business.
Creating a data-driven culture begins with the right hardware and software systems. Companies must take care to outfit their on-the-field infrastructure with the right sensors and IoT devices and must utilize state-of-the-art software to capture and analyze this data.
Companies also need to change their core business processes to directly relate to and manage this data. The technology has to be integrated at all levels of their field servicing so that data brought in and analyzed has an ultimate impact on when service calls are made and how service technicians operate.
Integrating data into field service is the first step towards making a more effective, productive, and competitive environment. Companies can substantially reduce their overhead while also reducing their risk, by utilizing an ecosystem that is less likely to experience breakdowns, delays, or injuries. For more information about this type of solution, contact the experts at Starr & Associates.
For many decades, the healthcare industry as a whole was able to maintain status quo. In the last decade alone, however, it’s experienced a great deal of disruption. From self-service healthcare and patient self-advocacy to predictive analytics and big data, the industry is changing. From small clinics to large healthcare organizations, businesses within this industry must change with it.
In predictive analytics, historical datasets are compiled and analyzed for patterns. Once patterns are found, this analytic data is used to make predictions on future outcomes. Predictive analytics can be used for a wide variety of scenarios, ranging from determining whether a customer might leave the organization to identifying the products and services a customer may be most interested in.
Predictive analytics has existed for as long as data has existed, but it isn’t up until recently that the raw, computational power necessary for making accurate guesses was available. Organizations now collect more data than ever before and can use this data to make surprisingly accurate predictions.
Patient-generated data can now be analyzed to diagnose a multitude of issues. As patients are continually becoming stronger advocates for their health, organizations are going to see an increase in self-service healthcare. Patients are going to be pursuing their own diagnosis and are going to be identifying their symptoms. Patients are also going to be studying their billing and their medical costs more intently.
In the past, it wasn’t always necessary for healthcare organizations to be proactive about transparency. Though patients have always had the right to their own healthcare data (and the agency to make their own decisions), it wasn’t always a priority that patients understand every step of the process. In the new medical landscape, patients are going to begin to demand to be equal partners in their health decisions.
To compete with these new, disruptive technologies, healthcare clinics are going to need to take steps towards creating a more patient-friendly system. Collecting data is only one small part of this; clinics will also need to be able to reliably analyze and protect this data, both regarding confidentiality and security.
As patients become more knowledgeable and forceful about their rights as a consumer, healthcare professionals are going to need to be more customer-centric and patient-focused. This may create a radical shift in many business processes and business operations, especially in terms of customer acquisition and retention.
Healthcare organizations are in for some significant and immediate change as the industry is in the process of being disrupted by new, advanced data technologies. At Starr & Associates, we can help. Contact us today to find out more about the disruption that could be headed for your business.
Modern businesses need to adapt to the speed at which technology changes. The past decade has seen a multitude of entrenched industries fall by the wayside in the wake of digital disruption. Businesses need to be proactive about following technological trends if they want to avoid potential disaster.
In our current society, technology doesn’t evolve slowly. True innovation appears on the scene and then suddenly explodes, completely supplanting whatever came before it. Big Bang Disruption is driven by new technologies; with advancements on all spectrums of technology, it’s easier for new technology to gain purchase.
Technology is consequently able to suddenly and thoroughly impact the economic market. With more affordable experimentation and information, companies are able to better innovate and to race towards technologies that are more likely to be lasting and helpful.
Organizations need to invest in change management to remain agile and active in this new, technologically explosive era. Change management has to be developed as a company-wide, multi-phase process. At all levels, employees have to be committed to change.
Traditionally, employees and upper management alike are reluctant to commit to change because they fear that this change will have a negative impact on operations. By promoting constant change and providing a positive reward system, employees can get past this negative perception.
To improve change management, it’s important that organizations be transparent about their change management processes and that they be clear about the value proposition for employees. It must be clear that a business will fail if the business does not continually change. The goals of each change must be thoroughly outlined.
Different industries have different rates of disruption. Much like other areas of risk management, it’s critical that you understand your industry’s likelihood of disruption before you begin making changes. If your business is in a low impact area, you may not need to invest as much into your change management processes. If you’re in a high-risk area, it’s absolutely critical that you do so.
When it comes to disruption, there are four important aspects: viability, volatility, durability, and vulnerability. Diversified chemicals, tires and rubber, and alcoholic beverages are all considered to be durable industries. On the other hand, the consumer technology, banking, and investment banking industries are experiencing volatility, as regulations and changing markets have shifted their operations.
Ultimately, disruption and change management may not be a process that can originate from within. Instead, businesses may need third-party help to develop the processes that their organization needs to continue to thrive. Contact us today at Starr & Associates to learn more about how we can help your business manage its change.
As new products are continually emerging in the marketplace, businesses are starting to shed many of their older, more cumbersome processes and procedures, focusing instead on lightweight product exploration and development.
