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Today, 53% of business leaders consider ERP as a priority investment. Yet, 40% of executives struggle to access, analyze and use enterprise enterprise and customer data due to the complexity of ERP systems.
Knowledge management can help overcome this challenge by providing a guideline to manage and use information in your ERP systems easily.
Therefore, in this article, we will cover what ERP knowledge management is, its use cases, case studies and benefits.What is ERP knowledge management?
Enterprise Resource Planning (ERP) knowledge management refers to effectively managing and utilizing the knowledge and information generated through an organization’s ERP system.
An ERP system is a software platform that integrates various business processes and functions, such as:
Customer relationship management.
ERP knowledge management involves capturing, organizing, storing, and sharing the knowledge and information generated through these processes.What are the benefits of ERP knowledge management?
There are several benefits of ERP knowledge management, including:
Improved decision-making: ERP knowledge management provides access to timely, accurate information to help decision-makers make more informed and strategic decisions.
Increased efficiency: ERP knowledge management can help streamline business processes and reduce redundant efforts by ensuring employees have access to the information needed to perform their tasks efficiently.
Enhanced collaboration: ERP knowledge management can foster collaboration among employees and departments, improving teamwork and productivity by providing a central location for knowledge sharing.
Higher quality output: ERP knowledge management can help ensure employees use the system correctly and efficiently, resulting in higher quality output and improved customer satisfaction.
Cost savings: By reducing the need for redundant efforts and improving overall efficiency, ERP knowledge management can lead to cost savings for the organization.
Improved employee satisfaction: ERP knowledge management can increase job satisfaction and employee retention by providing employees with the knowledge and tools they need to perform their jobs effectively.6 Use cases & Case Studies of ERP knowledge management
Here are 6 ways to use knowledge management for ERP:1. Create a centralized knowledge repository
All relevant knowledge related to your ERP system can be stored in a knowledge repository. These central knowledge locations can include user manuals, training materials, policies and procedures, best practices, FAQs, and troubleshooting guides. A central knowledge repository provides easy access ERP related information.
For example, Siemens AG, a global technology company, created a repository while implementing an ERP system to improve its financial management processes.2. Encourage knowledge sharing
92% of ERP-users in a survey complained about the difficulty of data sharing.
These efforts enable employees to raise questions, share their best practices and tips, and offer feedback to others. Such knowledge sharing provides a regular check on knowledge management best practices and improves how employees interact with ERP systems.3. Implement a continuous improvement process
Another common use case of ERP knowledge management is developing a continuous improvement cycle based on employee feedback and insights. Organizations can run regular surveys and organize user feedback sessions.
By analyzing employee experience, businesses can upgrade, update, and enhance their ERP system.4. Use analytics and metrics
Organizations develop metrics and analytics to enable data-driven decision-making in their business. The same approach can be implemented to measure the effectiveness of ERP knowledge management. Some of these metrics include:
User adoption rate tracking
User satisfaction measures
System performance monitoring (For more, see Figure 1).
These KPIs allow businesses to identify pain points and optimize ERP systems.
Figure 1: An example of KPIs for ERP management systems.5. Provide training programs
Figure 2 shows that lack of knowledge and skill training is the top reason ERP usage and performance have failed.
Figure 2: Survey results on ERP challenges
Organizations must develop training programs to ensure employees have the knowledge and skills to use their ERP systems effectively. These training programs may include:
Formal training sessions
Informal coaching and mentoring6. Help desk and support services
Organizations can create a system to provide constant services to assist users with their ERP system issues. Such support services can be in the form of:
For instance, Coca-Cola Enterprises (CCE) is the world’s largest bottler of Coca-Cola products, operating in 13 countries.Further reading
Learn more on knowledge management systems and tools:
Hazal is an industry analyst in AIMultiple. She is experienced in market research, quantitative research and data analytics. She received her master’s degree in Social Sciences from the University of Carlos III of Madrid and her bachelor’s degree in International Relations from Bilkent University.
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It takes 280 days to identify a cyberattack without the help of any intelligent tool. This is why AI in the cybersecurity market is estimated to reach $46.3 billion in 2027.
Cybersecurity protects computer systems and networks from data leaking, theft, damage, and disruption of services. Cybersecurity is challenging due to the variety and complexity of information systems. It can specifically struggle with processing data registered in IT systems.
Recently, process mining has been applied to solve this issue. Process mining can specify user-behavior anomalies and fraudulent activities in business operations by extracting and analyzing business process data.
Therefore, we will cover 12 use cases of process mining in cybersecurity.1. Security breaches
In 2023, data breach costs increased up to ~$4.24M and 58% of these data leaks included personal level information. One way to tackle this issue is to develop and apply security breach models.
Process mining can be useful for modeling and evaluating security breaches in a fast and data-driven manner. Also, typically security breaches target high-level activities, but process mining enables mapping both high and low-level operations to capture the interaction between these two levels.2. Industrial control systems
Industrial control systems (ICS) are widely used to produce, monitor and control for manufacturing, transportation, and utility sectors. The ICS security efforts intend to protect these systems from cyber attacks.Cyberattacks include risks such as information confidentiality, integrity of the process and safety to personnel and property.
Process mining can detect cyberattacks in these systems and compare noticed anomalous cases. Process mining can facilitate cybersecurity efforts since it can manage asset inventory, vulnerability, user access and patch, which are crucial activities in cybersecurity.3. IoT security
According to cybersecurity statistics, In 2023 alone, ~1.5 billion cyberattacks on IoT devices have been caught.
The major contribution of integrating process mining with IoT is to reduce the time and effort for detecting and modeling the attacks realized. Process mining can automatically model the attacks and determine whether an attack is new or belongs to the existing list by running a conformance check. Based on the result, the system can direct the latest outbreak to the security operator or provide information on the attack traces to take action immediately.4. Smart grids
Smart grids are operation and energy measures that target maintaining a reliable, secure, sustainable and efficient energy infrastructure. These grids are interconnected to network between producers and consumers. Cybersecurity aims to protect smart grids from user errors, equipment failures, natural disasters, espionage operations and terror attacks.
Process mining can improve cybersecurity by facilitating employee and user errors and failure detection. It also assesses compliance with grid policies and pinpoints abnormal energy usage.5. Smartphones
Smartphones are often under threat of data leaks and financial theft. The security system identifies and prevents unauthorized users’ access to the enterprise network to secure smartphones.
Process mining can seamlessly notice malware and identify specific attacks with conformance checking.6. Network traffic
Network traffic security monitors network activity to spot security and operational anomalies, such as ransomware. Analysts are expected to gather real-time data and historical network traffic records to achieve it.
Process mining can leverage network traffic data (e.g., DNS logs) to discover and visualize attacks, classify attacks based on the type, and detect unexpected behavior like spam attacks in network operations.7. Web-application
Web applications security concerns focus on breaches which can end up with service disruptions and data leaks.
Process mining generates a model of user behavior to catch malicious activities on social network websites. Process mining can also facilitate enforcing security policies by constantly monitoring the flow following the desired model.8. Attack inspection
Attack inspection focuses on understanding how a specific attack is performed. Attack inspection aims to help prevent future attacks.
Process mining can discover the attack process, compare successful and unsuccessful attacks, and assess the impact of protection measures for the given application software.9. Outlier user behavior
User behavior detection refers to the efforts to identify malicious user activities.
Process mining can deliver information about outlier user behaviour that is non-conforming and deviations because the software shows the entire process flow with relevant activities and people involved in the given organization.
Moreover, Process mining can be useful for multinational organizations or large enterprises with complex processes. With process mining, security teams can monitor the interaction across sub-processes in various departments and look for undesired behavior and deviations.10. Fraudulent activities
Such activities refer to processes that do not confirm a rule or policy and are commonly found in financial services and banking.
Process mining offers user-friendly dashboards and visualizations and provides deep and detailed analysis, which consists of control flow, time and resources. As a result, it helps place and visualize frauds.
For example, in a case study, process mining identified fraud in credit applications by identifying skipped events and violations of rules attributed to conformance checks.11. Quality assurance
Quality assurance (QA) aims to test the developed software and identify bugs and other problems before deployment. QA and cybersecurity are closely related because both deal with software vulnerability and weakness to manage and reduce risks.
Process mining ensures that services and software projects conform to the contract or ideal models by diagnosing bugs and assessing the conformance levels. As a result, it enables quality assurance and improve cybersecurity.12. Error detection
Error detection is the method to determine improper behavior and its root causes, specifically within the software system. It aims to assist in deployment and maintenance.
Process mining is widely used for error discovery in IT, service-oriented systems, and blockchain. Process mining can illustrate the deployment of the software as well. Consequently, it helps comprehend and predict problems occurring in that phase.
For instance, process mining can audit blockchain smart contracts or service behavior by monitoring configuration management. It can also verify the run time of the implemented IT system through conformance checks. Process mining pinpoints the root cause behind such problems and helps the system become more robust.Further reading
Explore other process mining use cases and real life examples in different industries and business functions:
Download our whitepaper on process mining, If you want to explore more on process mining benefits and how to choose a vendor:
Compare process mining software through our data-driven comprehensive process mining vendor list.
Assess different vendors with a transparent methodology yourself by downloading our checklist:
And, if you still have more questions, let us know:
Hazal is an industry analyst in AIMultiple. She is experienced in market research, quantitative research and data analytics. She received her master’s degree in Social Sciences from the University of Carlos III of Madrid and her bachelor’s degree in International Relations from Bilkent University.
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Within minutes of learning of an oil refinery fire on the West Coast, a salesperson from Equilon Enterprises LLC in Houston can turn to his company’s corporate portal, find out which customers are affected, and make sure he sells them the gas they need at current market prices. Five months ago that salesperson would have had to make a bunch of telephone calls and cruise various Internet sites to find that information.
AT A GLANCE: Equilon Enterprises LLC
The company: Houston-based Equilon Enterprises handles pipeline operations and gasoline distributions to all Texaco and Shell retail stations in the western United States. The company has 500 employees.
The problem: Need to increase the bottom line by bringing together disjointed technology and making information more Internet-centric.
The solution: Develop a corporate knowledge management portal that integrates all Equilon information into one central location on the desktop.
The technology: The portal runs on Windows NT servers from Compaq Computer Corp. and Hewlett-Packard Co. servers that run UNIX and Oracle 8i database.
But since Equilon, a joint venture of Shell Oil Co. and Texaco Inc., launched its corporate portal in June 2000, its salesforce and some account managers and pipeline schedulers now have access to much of the company’s internal data from one Web-enabled starting point. The portal integrates Equilon’s customer relationship management (CRM) system, suite of office software, and collaboration and document management tools, along with selected content, onto a single screen.
“It’s not so much that the information hasn’t been available, it’s the timeliness that the portal brings to us,” says Robert Stephens, an Equilon business information manager who helped implement the portal before leaving in September 2000 for another job. “We can get that information in real-time and make decisions quicker based on the information. It’s getting the right information to the right people at the right time.”
Equilon is among the growing number of firms launching corporate portals to help employees gather, manage, share, and utilize information that in the past had been stored in disparate databases throughout the company. These knowledge management portals not only bring the information to the employees’ fingertips through a corporate intranet site, or in some cases the Internet, but also help them interact with it, mine the data, and share information between one application and another.
Carl Frappaolo, executive vice president and cofounder of Delphi Group in Boston
The Evolving State of Corporate Portals
Dephi Group, which specializes in knowledge management research, estimates the corporate portal market by 2001 will grow to $740 million, from $178 million in 1999. By the beginning of next year, Delphi estimates nearly 90% of large organizations will be developing portals, with 80% in production mode. Similarly, Gartner Group Inc. of Stamford, Conn., estimates that by 2003, 50% of Fortune 1000 companies will have a knowledge management system in place. Both firms say there is a growing trend toward achieving knowledge management solutions through a portal interface.
“Knowledge management is a business process, not a technology,” says Jim Jacobs, Gartner Group knowledge management research director. “Portals are valuable technology that can assist with the business process.”
The idea is not just to gather information, but to present it so employees can interact with it and contribute back so others can learn from it, too. Software vendors began offering portal tools two years ago. Now more than 100 vendors have emerged, offering everything from niche tools to full, out-of-the-box solutions. However, there are no true leaders in this diversified space.
Lotus Development Corp. and Microsoft Corp. in October 2000 picked up the pace by announcing new knowledge management portal tools. Lotus’ K-station will work with collaborative tools such as Sametime, QuickPlace, and Domino to give users a single point of access to information. Microsoft announced a server application, code-named Tahoe, which will combine with its Digital Dashboard tools that are available for businesses that want to build their own portals.
Because there are so many portal vendors and the companies are so new, Gartner Group estimates there will be a shakeout in the industry by the middle of next year. “This is going to be a best-of-breed market,” says Jacobs. “We do not see a single vendor like Lotus dominating this space.”
While Delphi estimates the majority of large companies will be developing portals by next year, the types of portals will vary. A true knowledge management portal is one that brings together various data and technology systems from within a company and makes it easier for workers to gather and share information through a corporate intranet and online. The portal will allow workers to extract data that otherwise is hidden inside systems and oftentimes only available to the information technology staff.
“Knowledge resides between applications, not in applications itself,” says Delphi’s Frappaolo. “For example, give me a list of customers who have goals we’re not going to meet this week. When you start asking these complex questions, you don’t have a single place to answer the questions.”
Improving the Bottom Line
Companies are using knowledge management portals for different parts of their business. Office furniture manufacturer Herman Miller Inc. in 1995 embarked on a quest to use technology to improve its bottom line by reducing manufacturing lead time and increasing reliability for its customers. At the time, the Zeeland, Mich., company dealt with suppliers mainly by telephone and fax. An attempt to go through a third-party electronic data interchange had largely failed. So Herman Miller looked at portal software to bring all of its supply-chain data onto a single screen and make it accessible over the Internet to its suppliers.
Lessons Learned about Corporate Portals
1. Figure out what business problem you’re trying to solve, then go after a knowledge management solution that addresses that problem.
2. Check out portal providers carefully. There are more than 100, and the market is new. Many won’t be here two or three years from now.
3. Implement your knowledge management solution slowly to make sure it addresses the needs of users and to test how employees will use it.
4. A true knowledge management portal includes the ability to gather and feed data back into it, not just the ability of users to extract data. Make sure the system is able to accept and integrate new data back in.
After looking at different options through consultant Deloitte & Touche, Herman Miller chose to work with TopTier Software Inc., which offered a portal tool that allowed officials to integrate the company’s Baan enterprise resource planning (ERP) package with its browser. The portal includes payment information, invoices, demand, delivery, and quality control information about items ordered from Herman Miller. News and other Web information have also been integrated into the portal.
Brunsting says timely shipments to customers have improved because of the immediate cross communication between the suppliers and Herman Miller. “Five years ago we were averaging 75% [on-time shipments]; today we are consistently hitting 95% and above. We see the portal helping as one of the key enablers of getting that last 5%,” he says.
Delphi Group’s Frappaolo points to some Delphi clients that have implemented knowledge management portals to improve their businesses. AT&T uses its knowledge management portal for its international salesforce, reducing the time necessary to close deals. Scientists at Lawrence Livermore Labs in California use their portal to organize and access scientific information. And J.D. Edwards & Co. built a knowledge garden, which it uses to organize and disseminate business process and product information.
“[J.D. Edwards] achieved 1,080% return on investment in their ability to respond to complex [request for proposals] in a shorter period of time because the information was readily available,” Frappaolo says.
Insurance Companies Put Portals to Work
While some companies like Equilon and Herman Miller are well into their portal implementations, others like St. Paul Reinsurance, are just beginning. A member of insurance provider St. Paul Companies Inc., it is one of the first firms to beta test Lotus’s portal solution. By the end of the year the firm expects to begin rolling out its corporate portal, which will integrate corporate information, department information, and individual information into a series of screens. St. Paul Reinsurance uses Windows NT servers running on Compaq hardware.
“The vision is to provide collaboration capabilities and to allow people to organize their content and be able to control it in terms of how it gets authored, edited, approved, and published to the portal,” says Andrew Cole, senior vice president and chief information officer at St. Paul Reinsurance.
The portal will bring together Lotus Notes, Domino, chúng tôi Raven Enterprise Server, Microsoft Office applications, and anything from the Internet or St. Paul’s intranet. “If we have a merger and acquisition and are doing due diligence, people all over the world can meet in a knowledge window and feed in information,” says Cole. “It will be a repository of content on a given issue that lots of people can easily see. The knowledge worker doesn’t have to figure out where the content is located, or what format it is in, or what version it is. They just open up the knowledge window for that topic and there is the latest and greatest information at their fingertips.”
Equilon, meanwhile, by the end of the year expects to have more than 500 employees using the company’s portal. It integrates the firm’s CRM system from Siebel Systems Inc., collaboration software from OpenText Corp., and Microsoft’s suite of office products, including Outlook and Office. The system runs on Windows NT servers from Compaq Computer Corp. and Hewlett-Packard Co. servers that run UNIX and Oracle 8i database. By April 1, 2001, the portal will serve 2,500 employees and include Equilon’s SAP applications and the company’s geographical information system from Environmental Systems Research Institute Inc.
learn from it, too.“
Choosing the Best Portal Product
While no portal vendor has emerged as the leader, Gartner Group points to several that have promising software and vision (see “Portal Options” below). Among them are Corechange Inc., Datachannel Inc., Hummingbird Ltd., InfoImage Inc., Plumtree Software Inc., Sequoia Software Corp., SilverStream Software, Sybase Inc., TopTier Software, and Viador Inc. Companies offering niche products include Autonomy Inc., Brio Technology Inc., Epicentric Inc., Hyperwave Information Management Inc., Intraspect Software Inc., KnowledgeTrack Corp., Oracle Corp., Sagemaker Inc., and Verity Inc.
James Kobielus, collaboration and messaging analyst with The Burton Group in Midvale, Utah, says companies should look to their groupware vendors for knowledge management tools. “[Ask] how you can take that information and leverage it further, provide the information on your users, and give them the tools, applications, and data they need for knowledge management.”
Gartner’s Jacobs recommends that IT managers look at their business strategy and their current technology first. “The goal of the IT manager is not to implement exciting new technology, it’s to support the business process of your organization,” he says. “Be aware of the impact of technologies and the utility for them. Don’t wait for the magic bullet of technology to come along or look at the existing products as an automatic solution to their problems. There’s no easy answer, no quick fix.”
Plumtree Software Inc./Plumtree Corporate Portal 4.0, San Francisco
Lotus Development Corp./IBM Corp./K-Station, Boston
InfoImage Inc./Freedom, Phoenix
Viador Inc./e-Portal Framework, Mountain View, Calif.
Hummingbird Ltd./Enterprise Portal Suite, Toronto, Ontario
Sequoia Software Corp./XPS, Columbia, Md.
Sybase Inc. /Enterprise Portal, Emeryville, Calif.
TopTier Software/eBusiness Integration Portal, San Jose, Calif.
In 2023, having your online orders reach you “later than usual” wasn’t as surprising as it was back in 2023. From the automotive to the technology sector, the supply chain crisis has affected almost all industries.
A reason for the crisis is shipping issues. Another is producers not anticipating their diminishing stocks of intermediary goods. A McKinsey survey revealed that only 2% of smart device manufacturers, for instance, know when they will be able to source their subsequent batch of chips from their suppliers to use in their next production cycle (see Figure 1).
BOM (bill of materials) is a document that contains a detailed account of the type and number of intermediate inputs that go into the production process of a good. So having an accurate and up-to-date BOM is one way to gain deeper visibility into your supply chain. Using automation technologies, such as RPA, can help producers in that regard.
Figure 1: Only 2% of smart device manufacturers have visibility into higher supply chain tiers. Source: McKinseyWhat is a bill of material (BOM)?
A Bill of material (BOM) is a document that lays out the type and the quantity of needed intermediary goods to create a specific output.
Conceptually, a BOM is similar to a mathematical function that specifies how many inputs will result in the production of a certain amount of output (see Figure 2).
Figure 2: A BOM works similarly to a mathematical function. Image source: SSDIWhat is a real-life example of a BOM?
Figure 3 is an example of a BOM for a bicycle:
Level 0 is the finished product;
Level 1 contains the structural pieces of a bike (2 wheels, a handlebar, the main frame, etc.);
Level 2 contains the subcomponents that are housed atop the substructure (the seat, the grips, the rims, etc.).
The bike assembler schedules the production of the bike with respect to the delivery timeline and the sourcing of the parts. BOM is important because it gives the producer visibility into:
What exactly is needed,
How much of it is required,
The delivery of which part should take priority over the others,
And the sequence by which parts should be assembled.
For instance, it is quite meaningless if all the parts are sourced bar the actual bike frame to house everything on it. So the sourcing of the bike frame should take priority over, say, the handlebar grips. BOM contextualizes this.
Figure 3: A bicycle’s BOM. Image sourceWhat is RPA BOM?
Most of the steps that go into the creation, maintenance, and usage of BOM documents are rules-based and repetitive. The good news is that RPA can automate 70-80% of rules-based processes.
RPA BOM is setting up RPA bots, that do not require any APIs, and can connect with a company’s inventory management and supply chain management software, to automatically create and update their BOMs.
We will go into the specifics next.What are the use cases of RPA in BOM? 1. Accurate calculation of the required amount of input
Each product’s design sheet details the quantity and categories of intermediate goods needed to make it.
Same as with contract generation automation, companies can create standardized BOM templates, which RPA bots will then fill by extracting documents from the design sheet.
RPA bots can extract the product’s order amount and by combining the BOM’s and the order’s data, can calculate precisely how much of each intermediate good is needed.
The benefit will be a data-driven and error-free BOM that exactly tells the floor manager the quantity of goods and the types of tools he/she needs to create a finished product (see Figure 4).
Figure 4: IKEA’s assembly sheet can be considered a de-factor BOM for the consumer who is in charge of assembling intermediate products. Image source: Medium2. Digitized storage of the BOM
Cloud-based automation solutions allow you to store and access your BOMs on the cloud. This eliminates the need to keep physical records of BOMs.
Moreover, companies can leverage RPA-enabled chatbots that can allow managers, engineers, assemblers, and other relevant personnel to ask the chatbot to give them a specific BOM by providing its “name” or “ID number,” on demand and without having to manually search and look for it.3. Real-time stock monitoring
Smart shelves in retail are already being used.
Warehouses can equip their shelves with similar IoT sensors that:
Monitor, in real-time, the inventory levels of the intermediate goods,
And send an alert to the manager each time a certain item is picked off a shelf alongside the remaining stock.
RPAs can then be set up to extract each item’s remaining inventory level and include it on the BOM.
For instance, the BOM might indicate that to manufacture each computer monitor, one LCD panel is needed, and 12 of them are now in stock. That number would then decrease/increase every time it’s added to/taken off the shelf.
Companies can also program the RPA bots to send a notification to the purchasing manager whenever the inventory level of intermediate goods falls below a certain threshold, so they can approve an automatic reordering.4. Real-time shipping monitoring
Not all raw materials that go into the production of a product are sourced from nearby locations.
For instance, the parts that make up an Airbus A321, arrive from different regions across 4 different European countries (see Figure 5).
The outcome would be a BOM that not only specifies how many screws the assembly of a good needs, but also the real-time ETA of the next batch.
Fleet management is also becoming smarter these days, thanks to motion devices. So whenever there is the slightest of disruptions in the shipping trucks, for instance (i.e., a blown tire), the:
The software will adjust the ETA on the supply chain software automatically – your Google Maps increases your initial ETA too, whenever you stop on the side of the road.
And the RPA bot will update the product’s ETA on the BOM accordingly.
The benefit is that warehouse managers will know when to expect deliveries, so they can inform the sales team and prepare themselves to accept the deliveries accordingly.
Product updates are changes that producers make to a product after listening to consumers’ feedback. Product updates are usually small tweaks, such as changing the supplier, shape, or material of an intermediate good.
Let’s say a kitchen sink manufacturer decides to use polyester resins instead of phenolic resins because the former gives higher heat resistance to the sink. Once the change is made official, the design sheet and the BOM should immediately reflect the new changes.
RPA software can be configured to continuously monitor the company’s vendor list and the products they supply in order to flag any changes to either category. Therefore, the RPA bot can use its OCR capabilities to read the previous item on the BOM, delete it, and replace it with the new one as soon as the supplier of a given input changes, along with them, their supplied input, according to rules-based frameworks.
In addition, if the new input is more efficient and less of it is needed in the product, the bot can extract the new quantity from the design sheet and change the previous amount on the BOM.
Digitized storage of the BOM also makes compliance checks and audits more streamlined, accurate, and less stressful.
For instance, if safety inspectors visit the shop floor of an elevator manufacturer and ask for the specific quantity of the oil that the manufacturer puts in the elevator’s oil break, the RPA bot can provide it on command. Moreover, because the older versions are also archived digitally, the inspectors can compare and contrast the current levels with the previous ones to see improvement/deterioration.For more on RPA
To learn more about the use cases of RPA, read:
To gain a comprehensive insight into RPA, download our RPA whitepaper:
If you believe your business would benefit from adopting an RPa solution, head over to our RPA list to find a data-driven list of vendors.
Reach out to us to help you choose the best one based on your needs:
He primarily writes about RPA and process automation, MSPs, Ordinal Inscriptions, IoT, and to jazz it up a bit, sometimes FinTech.
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Although primarily protection and enhanced productivity in function, several iPhone accessories can be stylish too! If you take the case of iPhone protective cases, this can be perceived rightly, and that is the reason why there is never-ending demand for iPhone 6 cases, despite the sturdy build and un-matchable quality of the Apple device. If you’re an iPhone 6 user and want to protect your iPhone 6 using something cool, here you go — with our list of 15 cool iPhone 6 cases! We hope the list will be interesting for those stylish freaks out there, at least. So shall we start?1. TOTU Smart Window iPhone 6 Case
If you need an iPhone 6 case that covers all sides of the device, even when letting you know what you need using the Smart Window View feature, you should check out TOTU Smart Window iPhone 6 Case. Well, we do firmly think that using TOTU Smart Window iPhone 6 Case will change the typical look of your iPhone, which you have to never-mind! Some features that make TOTU Smart Window iPhone 6 Case include the in-built kickstand for enhanced viewing, its smart metal plate that lets you answer or refuse calls without opening the case etc.
Where to Buy: Amazon2. SwiftBox 3D Sports Car iPhone 6 Case
Where to Buy: Amazon3. Ace Teah Colourful Cover for iPhone 6
If you love colours and love changing them according to your daily senses, it will be a wise decision to go with the set of colourful iPhone 6 covers from Ace Teah. The pack includes nine covers, which you can attach and detach so easily that you would love to get the vividness. Keeping the design aspect aside, Ace Teah Colourful Cover for iPhone 6 has a lot of protection features too, such as the raised lip and bevelled edges. Altogether, it’s a good deal, we think.
Where to Buy: Amazon4. Sahara Black iPhone 6 Case
Sahara Black iPhone 6 Case is indeed a cool iPhone 6 Case, given the combination of grey and black design elements it comes with. Apart from giving your iPhone 6 a touch of majestic black style, Sahara Black iPhone 6 Case offers a lot of protection-oriented features as well, which include the tempered glass screen protector, slim yet effective level of protection, use of TPU edges to lessen impact of shocks etc. Considering all these and the price, Sahara Black iPhone 6 Case is worth the buy.
Where to Buy: Amazon5. ULAK Chrome iPhone 6 Case
Made of high-quality building materials, keeping in mind an impressive design notion, ULAK Chrome iPhone 6 Case is capable of impressive everyone who likes to give their iPhone 6 a luxury style of look, without, actually, affecting the look of iPhone 6 Smartphone. Although ULAK Chrome iPhone 6 Case comes in different colours, we loved Silver one, for the style it provides is truly stunning! Along with the design stuff, ULAK Chrome iPhone 6 Case offers a good level of protection as well.
Where to Buy: Amazon6. Wisdompro iPhone 6 Case Bundle
Just as the case of the product from Ace Teah, here comes another bundle of stunning iPhone 6 cases, in colours that the world call girly — screw the stereotypes! The protective case comes in five colours such as Blue, Aqua Blue, Red, Yellow and Hot Pink. All these cases are made of soft TPU and has enough strength to protect from normal drops and shocks. Also, when you buy the Wisdompro iPhone 6 Case Bundle, you get a universal stylus and cleaning cloth that would be useful.
Where to Buy: Amazon7. Anker Ultra Slim iPhone 6 Case
Where to Buy: Amazon8. New Trent iPhone 6 Case
New Trent iPhone 6 Case is a good choice if you’d like to give your iPhone 6 an unfamiliar look! This protective case has been made using a transparent material, and thus protecting the actual style of your iPhone 6 case, even though it does not affect protection-oriented features of capacity. Thanks to transparent device, you can make your iPhone 6 glow if you set up LED Flash alerts for the notifications you receive. The rugged case, in addition to these, has edge design that is meant to drop protection.
Where to Buy: Amazon9. Yousave Accessories Raindrop iPhone 6 Case
If you like rain, or at least the design of it, you would love to check out Yousave Accessories Raindrop iPhone 6 Case, which is available at a rather affordable rate. Apart from the impressive protection that is offered by the hard case, it includes screen protector that is clear enough to give a good viewing experience. In addition to all the stuff, Yousave Accessories Raindrop iPhone 6 Case has perfect cut outs, keeping comfortable use in mind.
Where to Buy: Amazon10. Mallom Cute Owl Hard Back Case for iPhone 6
Mallom Cute Owl Hard Back Case for iPhone 6 will be a good option if you won’t mind seeing owl looking at you with its typical look, at the back side of your iPhone 6. Probably the most affordable cool iPhone 6 case in list, the Mallom Cute Owl Hard Back Case for iPhone 6 protects the iPhone from scratches, shatter, shocks etc. Altogether, when you are looking for an affordable iPhone 6 case that does not affect signal strength or does other mess-up, you will find it a good option.
Where to Buy: Amazon11. ChiChiC Stylish TPU iPhone 6 Case
With dreamy background in the back side of your iPhone 6 — never mind if someone calls you a dreamer —, ChiChiC Stylish TPU iPhone 6 Case is a good deal, indeed, given that you have a mediocre budget to keep. This case made of TPU has a number of features such as the unmatchable art design, impressive user experience, and compatability with almost every popular cellular carrier. Also, the material used for the production of ChiChiC Stylish TPU iPhone 6 Case is truly durable, due to the high-quality.
Where to Buy: Amazon12. MagicMobile iPhone 6 Case
Where to Buy: Amazon13. Bessky Soft TPU Case for iPhone 6
Bessky Soft TPU Case for iPhone 6 comes with a dream catcher design at the back side of the case, giving the iPhone 6 a royal look that is capable of impressing almost everyone out there. This high quality, metal shell make of the case is effective in terms of the looks as well as the sturdy protection the case provides to the Smartphone, particularly if you take its price into the account. So, in the long run, Bessky Soft TPU Case for iPhone 6 is a good deal.
Where to Buy: Amazon14. HOTCOOL Apple iPhone 6 Case
HOTCOOL Apple iPhone 6 Case is a great product for your iPhone 6, especially if you are looking for a transparent yet powerful case that will not affect the beauty of your iPhone 6 at any cost. Although the covering is thin enough, the case offers unmatchable power of security, along with the non-slip secure grip and other features. Considering all of these features, HOTCOOL Apple iPhone 6 Case is a steal-deal, given the truly affordable price.
Where to Buy: Amazon15. Tech Armour iPhone 6 Case
Tech Armour iPhone 6 Case offers a cool look to your iPhone 6 even while offering a never-compromised level of top protection for different aspects of the device. Made using a polycarbonate / TPU layer, Tech Armour iPhone 6 Case is capable of protecting the device from common damages such as drops, dust, dirt etc. of course, you will have to pay a bit more for the rugged durability!
Where to Buy: Amazon
SEE ALSO: 15 Best Waterproof iPhone 6 Cases
AI is changing every industry and business function, which results in increased interest in AI, its subdomains, and related fields such as machine learning and data science as seen below. With the launch of ChatGPT, interest in generative AI, a subfield of AI, exploded.
According to a recent McKinsey survey, 56% of organizations are using AI in at least one business function. To integrate AI into your own business, you need to identify how AI can serve your business, possible use cases of AI in your business. This article gathers the most common use cases covering marketing, sales, customer services, security, data, technology, and other processes:Generative AI
Generative AI involves AI models generating output in requests where there is not a single right answer (e.g. creative writing). Since the launch of ChatGPT, it has been exploding in popularity. Its use cases include content creation for marketing, software code generation, user interface design and many others.
For more: Generative AI use cases.Business Functions General solutions
Analytics Services: Satisfy your custom analytics needs with these e2e solution providers. Vendors are there to help you with your business objectives by providing turnkey solutions.
Automated Machine Learning (autoML): Machines helping data scientists optimize machine learning models. With the rise of data and analytics capabilities, automation is needed in data science. AutoML automates time consuming machine learning tasks, enabling companies to deploy models and automate processes faster.Specialized solutions
Conversational Analytics: Use conversational interfaces to analyze your business data. Natural Language Processing is there to help you with voice data and more enabling automated analysis of reviews and suggestions.
E-Commerce Analytics: Specialized analytics systems designed to deal with the explosion of e-commerce data. Optimize your funnel and customer traffic to maximize your profits.
Geo-Analytics Platform: Enables analysis of granular satellite imagery for predictions. Leverage spatial data for your business goals. Capture the changes in any landscape on the fly.
Real-Time Analytics: Real-Time Analytics for your time-sensitive decisions. Act timely and keep your KPI’s intact. Use machine learning to explore unstructured data without any disruptions.
Call Analytics: Advanced analytics on call data to uncover insights to improve customer satisfaction and increase efficiency. Find patterns and optimize your results. Analyze customer reviews through voice data and pinpoint, where there is room for improvement. Sestek indicates that ING Bank observed a 15% increase in sales quality score and a 3% decrease in overall silence rates after they integrated AI into their call systems.
Call Classification: Leverage natural language processing (NLP) to understand what the customer wants to achieve so your agents can focus on higher value-added activities. Before channeling the call, identify the nature of your customers’ needs and let the right department handle the problem. Increase efficiency with higher satisfaction rates.
Call Intent Discovery: Leverage Natural Language Processing and machine learning to estimate and manage customer’s intent (e.g., churn) to improve customer satisfaction and business metrics. Sentiment analysis through the customer’s voice level and pitch. Detect the micro-emotions that drive the decision-making process. Explore how chatbots detect customer intent in our in-depth article on intent recognition.
Chatbot for Customer Service (Self – Service Solution): Chatbots can understand more complicated queries as AI algorithms improve. Build your own 24/7 functioning, intelligent, self-improving chatbots to handle most queries and transfer customers to live agents when needed. Reduce customer service costs and increase customer satisfaction. Reduce the traffic on your existing customer representatives and make them focus on the more specific needs of your customers. Read for more insights on chatbots in customer service or discover chatbot platforms.
Chatbot Analytics: Analyze how customers are interacting with your chatbot. See the overall performance of your chatbot. Pinpoint its shortcomings and improve your chatbot. Detect the overall satisfaction rate of your customer with the chatbot.
Chatbot testing: Semi-automated and automated testing frameworks facilitate bot testing. See the performance of your chatbot before deploying. Save your business from catastrophic chatbot failures. Detect the shortcomings of your conversational flow.
Customer Contact Analytics: Advanced analytics on all customer contact data to uncover insights to improve customer satisfaction and increase efficiency. Utilize Natural Language Processing for higher customer satisfaction rates.
Customer Service Response Suggestions: Bots will listen in on agents’ calls suggesting best practice answers to improve customer satisfaction and standardize customer experience. Increase upsells and cross-sells by giving the right suggestion. Responses will be standardized, and the best possible approach will serve the benefit of the customer.
Social Listening & Ticketing: Leverage Natural Language Processing and machine vision to identify customers to contact and respond to them automatically or assign them to relevant agents, increasing customer satisfaction. Use the data available in social networks to uncover whom to sell and what to sell.
Intelligent Call Routing: Route calls to the most capable agents available. Intelligent routing systems incorporate data from all customer interactions to optimize the customer satisfaction. Based on the customer profile and your agent’s performance, you can deliver the right service with the right agent and achieve superior net promoter scores. Feel free to read case studies about matching customer to right agent in our emotional AI examples article.
Survey & Review Analytics: Leverage Natural Language Processing to analyze text fields in surveys and reviews to uncover insights to improve customer satisfaction and increase efficiency. Automate the process by mapping the right keywords with the right scores. Make it possible to lower the time for generating reports. Protobrand states that they used to do review analytics manually through the hand-coding of the data, but now it automates much of the analytical work with Gavagai. This helps the company to collect larger quantitative volumes of qualitative data and still complete the analytical work in a timely and efficient manner. You can read more about survey analytics from our related article.
Voice Authentication: Authenticate customers without passwords leveraging biometry to improve customer satisfaction and reduce issues related to forgotten passwords. Their unique voice id will be their most secure key for accessing confidential information. Instead of the last four digits of SSN, customers will gain access by using their voice.
Data Cleaning & Validation Platform: Avoid garbage in, garbage out by ensuring the quality of your data with appropriate data cleaning processes and tools. Automate the validation process by using external data sources. Regular maintenance cleaning can be scheduled, and the quality of the data can be increased.
Data Integration: Combine your data from different sources into meaningful and valuable information. Data traffic depends on multiple platforms. Therefore, managing this huge traffic and structuring the data into a meaningful format will be important. Keep your data lake available for further analysis.
Data Preparation Platform: Prepare your data from raw formats with data quality problems to a clean, ready-to-analyze format. Use extract, transform, and load (ETL) platforms to fine-tune your data before placing it into a data warehouse.
Data Visualization: Visualize your data for better analytics and decision-making. Let the dashboards speak. Convey your message more easily and more esthetically.
Data Labeling: Unless you use unsupervised learning systems, you need high quality labeled data. Label your data to train your supervised learning systems. Human-in-the-loop systems auto label your data and crowdsource labeling data points that cannot be auto-labeled with confidence.
Synthetic Data: Computers can artificially create synthetic data to perform certain operations. The synthetic data is usually used to test new products and tools, validate models, and satisfy AI needs. Companies can simulate not yet encountered conditions and take precautions accordingly with the help of synthetic data. They also overcome the privacy limitations as it doesn’t expose any real data. Thus, synthetic data is a smart AI solution for companies to simulate future events and consider future possibilities. You can have more information on synthetic data from our related article.
Finance business function led by the CEO completes numerous repetitive tasks involving quantitative skills which makes them a good fit for AI transformation:
Billing / invoicing reminders: Leverage accessible billing services that remind your customers to pay.
Invoicing: Invoicing is a highly repetitive process that many companies perform manually. This causes human errors in invoicing and high costs in terms of time, especially when a high volume of documents needs to be processed. Thus, companies can handle these repetitive tasks with AI, automate invoicing procedures, and save significant time while reducing invoicing errors.
Employee Monitoring: Monitor your employees for better productivity measurement. Provide objective metrics to see how well they function. Forecast their overall performance with the availability of massive amounts of data.
Hiring: Hiring is a prediction game: Which candidate, starting at a specific position, will contribute more to the company? Machine and recruiting chatbots‘ better data processing capabilities augment HR employees in various parts of hiring such as finding qualified candidates, interviewing them with bots to understand their fit or evaluating their assessment results to decide if they should receive an offer.
HR Analytics: HR analytics services are like the voice of employee analysis. Look at your workforce analytics and make better HR decisions. Gain actionable insights and impactful suggestions for higher employee satisfaction.
HR Retention Management: Predict which employees are likely to churn and improve their job satisfaction to retain them. Detect the underlying reasons for their motive for seeking new opportunities. By keeping them at your organization, lower your human capital loss.
Performance Management: Manage your employees’ performance effectively and fairly without hurting their motivation. Follow their KPI’s on your dashboard and provide real-time feedback. This would increase employee satisfaction and lower your organization’s employee turnover. Actualize your employee’s maximum professional potential with the right tools.
You can also read our article on HR technology trends.
A 2023 survey conducted among global marketers revealed that 41% of respondents saw an increase in revenue growth and improved performance due to the use of AI in their marketing campaigns.
Marketing can be summarized as reaching the customer with the right offer, the right message, at the right time, through the right channel, while continually learning. To achieve success, companies can leverage AI-powered tools to get familiar with their customers better, create more compelling content, and perform personalized marketing campaigns. AI can provide accurate insights and suggest smart marketing solutions that would directly reflect on profits with customer data. You can find the top three AI use cases in marketing:
Marketing analytics: AI systems learn from, analyze, and measure marketing efforts. These solutions track media activity and provide insights into PR efforts to highlight what is driving engagement, traffic, and revenue. As a result, companies can provide better and more accurate marketing services to their customers. Besides PR efforts, AI-powered marketing analytics can lead companies to identify their customer groups more accurately. By discovering their loyal customers, companies can develop accurate marketing strategies and also retarget customers who have expressed interest in products or services before. Feel free to read more about marketing analytics with AI from this article.
To learn more about AI use cases in marketing, you can check out our complete guide on the topic.Admin
Digital Assistant: Digital assistants are mature enough to replace real assistants in email communication. Include them in your emails to schedule meetings. They have already scheduled hundreds of thousands of meetings.Pre-Sales
Sales Forecasting: AI allows automatic and accurate sales forecasts based on all customer contacts and previous sales outcomes. Automatically forecast sales accurately based on all customer contacts and previous sales outcomes. Give your sales personnel more sales time while increasing forecast accuracy. Hewlett Packard Enterprise indicates that it has experienced a 5x increase in forecast simplicity, speed, and accuracy with Clari’s sales forecasting tools.Sales
Sales Data Input Automation: Data from various sources will be effortlessly and intelligently copied into your CRM. Automatically sync calendar, address book, emails, phone calls, and messages of your salesforce to your CRM system. Enjoy better sales visibility and analytics while giving your sales personnel more sales time.
AI-based agent coaching: Both AI and emotion AI can be leveraged to coach sales reps and customer service employees by:
Retail Sales Bot: Use bots on your retail floor to answer customer’s questions and promote products. Engage with the right customer by analyzing the profile. Computer vision will help you to provide the right action depending on the characteristics and mimics of the customer.
Meeting Setup Automation (Digital Assistant): Leave a digital assistant to set up meetings freeing your sales reps time. Decide on the targets to prioritize and keep your KPI’s high.
Prescriptive Sales: Most sales processes exist in the mind of your sales reps. Sales reps interact with customers based on their different habits and observations. Prescriptive sales systems prescribe the content, interaction channel, frequency, price based on data on similar customers.
Conversational AI company Haptik develops sales chatbots for companies, including Fortune 500 ones, to improve their conversational commerce capabilities. For instance, thanks to Haptik’s sales chatbot, Tata Cliq, an e-commerce platform, increased its cart addition rate by 2.4 times in three months.Sales analytics
As Gartner discusses, sales analytic systems provide functionality that supports discovery, diagnostic, and predictive exercises that enable the manipulation of parameters, measures, dimensions, or figures as part of an analytic or planning exercise. AI algorithms can automate the data collection process and present solutions to improve sales performance. To have more detailed information, you can read our article about sales analytics.
Customer Sales Contact Analytics: Analyze all customer contacts, including phone calls or emails, to understand what behaviors and actions drive sales. Advanced analytics on all sales call data to uncover insights to increase sales effectiveness
Sales Call Analytics: Advanced analytics on call data to uncover insights to increase sales effectiveness. See how well your conversation flow performs. Integrating data on calls will help you to identify the performance of each component in your sales funnels.
Sales attribution: Leverage big data to attribute sales to marketing and sales efforts accurately. See which step of your sales funnel performs better. Pinpoint the low performing part by the insights provided by analysis.
Sales Compensation: Determine the right compensation levels for your sales personnel. Decide on the right incentive mechanism for the sales representatives. By using the sales data, provide objective measures, and continuously increase your sales representatives’ performance.
For more details on how AI is changing sales, you can check out our more comprehensive guide.
No code AI & app development: AI and App development platforms for your custom projects. Your in-house development team can create original solutions for your specific business needs.
Analytics & Predictive Intelligence for Security: Analyze data feeds about the broad cyber activity as well as behavioral data inside an organization’s network to come up with actionable insights to help analysts predict and thwart impending attacks. Integrate external data sources the watch out for global cyber threats and act timely. Keep your tech infrastructure intact or minimize losses.
Knowledge Management: Enterprise knowledge management enables effective and effortless storage and retrieval of enterprise data, ensuring organizational memory. Increased collaboration by ensuring the right people are working with the right data. Seamless organizational integration through knowledge management platforms.
Natural Language Processing Library/ SDK/ API: Leverage Natural Language Processing libraries/SDKs/APIs to quickly and cost-effectively build your custom NLP powered systems or to add NLP capabilities to your existing systems. An in-house team will gain experience and knowledge regarding the tools. Increased development and deployment capabilities for your enterprise.
Image Recognition Library/ SDK/ API: Leverage image recognition libraries/SDKs/APIs to quickly and cost-effectively build your custom image processing systems or to add image processing capabilities to your existing systems.
Autonomous Cybersecurity Systems: Utilize learning systems to efficiently and instantaneously respond to security threats, often augmenting the work of security analysts. Lower your risk of human errors by providing greater autonomy for your cybersecurity. AI-backed systems can check compliance with standards.
Smart Security Systems: AI-powered autonomous security systems. Functioning 24/7 for achieving maximum protection. Computer vision for detecting even the tiniest anomalies in your environment. Automate emergency response procedures by instant notification capabilities.
Machine Learning Library/ SDK/ API: Leverage machine learning libraries/SDKs/APIs to quickly and cost-effectively build your custom learning systems or to add learning capabilities to your existing systems.
AI Developer: Develop your custom AI solutions with companies experienced in AI development. Create turnkey projects and deploy them to the specific business function. Best for companies with limited in-house capabilities for artificial intelligence.
Deep Learning Library/ SDK/ API: Leverage deep learning libraries/SDKs/APIs to quickly and cost-effectively build your custom learning systems or to add learning capabilities to your existing systems.
Developer Assistance: Assist your developers using AI to help them intelligently access the coding knowledge on the web and learn from suggested code samples. See the best practices for specific development tasks and formulate your custom solution. Real-time feedback provided by the huge history of developer mistakes and best practices.
AI Consultancy: Provides consultancy services to support your in-house AI development, including machine learning and data science projects. See which units can benefit most from AI deployment. Optimize your artificial intelligence spending for the best results from the insight provided by a consultant.Industries
Autonomous things including cars and drones are impacting every business function from operations to logistics.
Driving Assistant: Required components and intelligent solutions to improve rider’s experience in the car. Implement AI-Powered vehicle perception solutions for the ultimate driving experience.
Vehicle Cybersecurity: Secure connected and autonomous cars and other vehicles with intelligent cybersecurity solutions. Guarantee your safety by hack-proof mechanisms. Protect your intelligent systems from attacks.
Vision Systems: Vision systems for self-driving cars. Integrate vision sensing and processing in your vehicle. Achieve your goals with the help of computer vision.
Self-Driving Cars: From mining to manufacturing, self-driving cars/vehicles are increasing the efficiency and effectiveness of operations. Integrate them into your business for greater efficiency. Leverage the power of artificial intelligence for complex tasks.
For more: Generative AI applications in education
For more: Generative AI applications in fashion
Patient Data Analytics: Analyze patient and/or 3rd party data to discover insights and suggest actions. Greater accuracy by assisted diagnostics. Lower the mortality rates and increase patient satisfaction by using all the diagnostic data available to detect the underlying reasons for the symptoms.
Personalized Medications and Care: Find the best treatment plans according to patient data. Provide custom-tailored solutions for your patients. By using their medical history, genetic profile, you can create a custom medication or care plan.
Drug Discovery: Find new drugs based on previous data and medical intelligence. Lower your R&D cost and increase the output — all leading to greater efficiency. Integrate FDA data, and you can transform your drug discovery by locating market mismatches and FDA approval or rejection rates.
Real-Time Prioritization and Triage: Prescriptive analytics on patient data enabling accurate real-time case prioritization and triage. Manage your patient flow by automatization. Integrate your call center and use language processing tools to extract the information, priorate patients that need urgent care, and lower your error rates. Eliminate error-prone decisions by optimizing patient care.
Early Diagnosis: Analyze chronic conditions leveraging lab data and other medical data to enable early diagnosis. Provide a detailed report on the likelihood of the development of certain diseases with genetic data. Integrate the right care plan for eliminating or reducing the risk factors.
Assisted or Automated Diagnosis & Prescription: Suggest the best treatment based on the patient complaint and other data. Put in place control mechanisms that detect and prevent possible diagnosis errors. Find out which active compound is most effective against that specific patient. Get the right statistics for superior care management.
Pregnancy Management: Monitor mother and fetus health to reduce mothers’ worries and enable early diagnosis. Use machine learning to uncover potential risks and complications quickly. Lower the rates of miscarriage and pregnancy-related diseases.
Medical Imaging Insights: Advanced medical imaging to analyze and transform images and model possible situations. Use diagnostic platforms equipped with high image processing capabilities to detect possible diseases.
Healthcare Market Research: Prepare hospital competitive intelligence by tracking market prices. See the available insurance plans, drug prices, and many more public data to optimize your services. Leverage NLP tools to analyze the vast size of unstructured data.
Healthcare Brand Management and Marketing: Create an optimal marketing strategy for the brand based on market perception and target segment. Tools that offer high granularity will allow you to reach the specific target and increase your sales.
Gene Analytics and Editing: Understand genes and their components and predict the impact of gene edits.
Device and Drug Comparative Effectiveness: Analyze drug and medical device effectiveness. Rather than just using simulations, test on other patient’s data to see the effectiveness of the new drug, compare your results with benchmark drugs to make an impact with the drug.
Healthcare chatbot: Use a chatbot to schedule patient appointments, give information about certain diseases or regulations, fill in patient information, handle insurance inquiries, and provide mental health assistance. You can also use intelligent automation with chatbot capabilities.
For more, feel free to check our article on the use cases of AI in the healthcare industry.
Manufacturing Analytics: Also called industrial analytics systems, these systems allow you to analyze your manufacturing process from production to logistics to save time, reduce cost, and increase efficiency. Keep your industry effectiveness at optimal levels.
Collaborative Robots: Cobots provide a flexible method of automation. Cobots are flexible robots that learn by mimicking human workers’ behavior.
Network investment optimization: Both wired and wireless operators need to invest in infrastructure like active equipment or higher bandwidth connections to improve Quality of Service (QoS). Machine learning can be used to identify highest ROI investments that will result in less churn and higher cross and up-sell.Other
This was a list of areas by business function where out-of-the-box solutions are available. However, AI, like software, has too many applications to list here. You can also take a look at our AI in business article to read about AI applications by industry. Also, feel free to check our article on AI services.
It is important to get started fast with high impact applications and generate business value without spending months of effort. For that, we recommend companies to use no code AI solutions to quickly build AI models.
Once companies deploy a few models to production, they need to take a deeper look at their AI/ML development model.
We examined the pros and cons of this approaches in our article on making the build or buy decisions regarding AI.
You can also check out our list of AI tools and services:
These articles about AI may also interest you:
And if you have a specific business challenge, we can help you find the right vendor to overcome that challenge:
Sources: Though most use cases have been categorized based on our experience, we also took a look at some sources before finalizing the list:
Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.
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