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What are the Common Errors in Automation Implementation and How to Avoid Them

Automation is a buzzword in the business world today, promising increased efficiency, reduced human error, and cost savings. While automation has the potential to revolutionize processes, it’s not without its pitfalls. In this article, we’ll explore the common errors in automation implementation and provide insights on how to avoid them.

Introduction to Automation Implementation

Automation involves using technology to perform tasks with minimal human intervention. It has become a cornerstone of modern business operations, enabling companies to streamline processes, enhance productivity, and deliver superior customer experiences. Businesses across industries are increasingly embracing automation to stay competitive. It allows companies to save time and resources while improving accuracy and consistency. However, reaping the benefits of automation requires careful planning and execution.

 

Common Errors in Automation Implementation

 

  • Lack of Clear Objectives and Planning: One of the most common mistakes in automation implementation is a lack of clear objectives and a well-defined plan. Without a roadmap, organizations risk implementing automation in a haphazard manner, which can lead to inefficiency and confusion.

 

  • Choosing the Wrong Automation Tools: Selecting the right automation tools is crucial. Making the wrong choice can result in an incompatible system that doesn’t meet the organization’s needs. It’s essential to thoroughly research and assess options before making a decision.

 

  • Insufficient Employee Training: Employees are a critical part of the automation process. Inadequate training can lead to resistance and errors. Providing comprehensive training ensures a smooth transition and ongoing success.

 

  • Ignoring Scalability and Flexibility: Automation systems should be scalable and flexible to accommodate future growth and changing needs. Failing to consider scalability can result in costly system replacements.

 

  • Overlooking Data Security Concerns: Data security is paramount in today’s digital landscape. Neglecting security measures can lead to data breaches and legal issues. Ensure that automation systems have robust security features.

 

  • Poor Integration with Existing Systems: Inefficient integration can disrupt existing workflows and lead to data silos. Ensure that automation systems seamlessly integrate with the organization’s current technologies.

 

  • Failing to Monitor and Evaluate Automation Processes: Once automation is in place, continuous monitoring and evaluation are necessary. Ignoring this step can result in inefficiencies going unnoticed and unaddressed.

 

Best Practices to Avoid Automation Errors

 

  • Establishing Clear Goals and Objectives: To avoid automation pitfalls, set clear goals and objectives for the implementation process. This helps keep the entire organization aligned and focused on the desired outcomes.

 

  • Selecting the Right Automation Tools: Thoroughly assess and select the automation tools that best match your requirements. Choose tools that are user-friendly, compatible, and adaptable.

 

  • Ongoing Training and Adaptation: Continuous training and adaptation are essential to ensure that employees are well-versed in the automated processes and can adapt to changes.

 

  • Prioritizing Security and Data Protection: Place a high priority on data security and protection. Regularly update and test security measures to safeguard sensitive information.

 

  • Efficient Integration Strategies: Work on seamless integration with existing systems to ensure a smooth flow of data and processes within the organization.

 

  • Continuous Monitoring and Evaluation: Regularly monitor and evaluate automated processes to identify areas for improvement and optimization.

 

Conclusion

In conclusion, automation can bring remarkable benefits to businesses, but only if implemented correctly. By avoiding common errors listed above, organizations can make automation work for them. Follow best practices, including clear goal-setting, right tool selection, ongoing training, prioritizing security, efficient integration, and continuous monitoring, to ensure a successful automation journey.

Automation with Artificial Intelligence

Automation with Artificial Intelligence (AI) is transforming the way businesses operate by streamlining processes and reducing costs. It’s is increasingly being used by businesses to improve productivity in a variety of ways. AI can automate repetitive and time-consuming tasks, such as data collection and analysis, pattern recognition, predictive maintenance, fraud detection & customer service which frees up employees to focus on more complex tasks that require human decision-making and creativity such as strategic planning and decision-making. AI’s ability to learn and adapt makes it an indispensable tool in streamlining work processes, increase productivity and accuracy while reducing overhead costs. For example, a chatbot powered by AI can provide 24/7 customer support at a fraction of the cost of human customer service representatives.

 

When used together, automation and AI can supercharge your business. Below are some ways in which AI can be a game-changer for your business operations and increase productivity:

 

Natural Language Processing (NLP): NLP is a branch of AI that enables machines to understand and interpret human language. NLP can be used to automate customer service inquiries, such as chatbots, which can quickly and efficiently respond to common questions and issues.

Robotic Process Automation (RPA): RPA is a type of software that can be used to automate repetitive tasks. For example, an RPA bot can be programmed to extract data from invoices, input it into a database, and create reports.

Predictive Analytics: Predictive analytics is a branch of AI that uses algorithms to analyze historical data and make predictions about future trends. This can be used to automate tasks such as forecasting demand, scheduling maintenance, and predicting equipment failures.

Image Recognition: Image recognition is a type of AI that enables machines to recognize and interpret visual data. This can be used to automate tasks such as quality control, where machines can detect defects in products and reject them automatically.

Autonomous Vehicles: Autonomous vehicles are a type of AI-powered automation that can be used to transport goods and people without human intervention. This can be used to increase efficiency and reduce costs in industries such as logistics and transportation.

Overall, AI-powered automation can help businesses save time and money, improve efficiency and accuracy, and reduce the risk of errors and mistakes.

 

How to Implement Automation with Artificial Intelligence

Implementing automation with artificial intelligence (AI) requires a systematic approach that involves several steps. Here is a general outline of the process:

Define the tasks you want to automate. Automation with AI can be used for a variety of tasks, so it’s important to identify the specific tasks you want to automate. This will help you determine which AI technologies to use and how to best configure them. Consider the potential benefits of automation, such as increased efficiency, accuracy, and cost savings.

Gather data: AI algorithms need data to learn and make decisions. Collect and organize the relevant data for the tasks you want to automate.

Choose the right AI technology: There are a variety of AI technologies available, such as machine learning, natural language processing, and computer vision, each with its own strengths and weaknesses. Be sure to choose the right technology for the task at hand.

Configure the AI technology properly: Once you’ve chosen the right AI technology, it’s important to configure it properly. This includes setting up the training data and parameters needed for the AI technology to function properly.

Integrate with existing systems: To make the most of automation, you need to integrate the AI algorithms with your existing systems. This may involve working with APIs or other integration tools.

Test and evaluate the results: After you’ve implemented automation with artificial intelligence, be sure to test and evaluate the results. This will help you ensure that the AI technology is working as intended and that it’s providing benefits for your business.

Deploy and monitor: Once you are satisfied with the system’s performance, you can deploy it. However, automation systems are not set-and-forget solutions; you need to monitor them regularly to ensure that they continue to work well and make improvements as necessary.

 

Automation with AI is an increasingly popular trend and one that will have far-reaching implications for businesses, industries, and economies in the future. With AI capabilities, organizations can not only reduce their costs but also increase their efficiency and gain a competitive advantage in the marketplace. The potential of automation powered by AI is limitless and provides us with many exciting opportunities to push the existing technology forward.

RPA: Why should you consider automation to achieve operational excellence

reasons to start with RPA AUTOMATION

As we are moving towards rapid development, every business is becoming “intelligent” and constantly finding new ways to reinvent their products and services, amaze their customers, and increase profits. To survive in today’s competitive world, companies of all shapes and sizes are integrating automation into their infrastructure, some of them succeed while others fail. According to Forrester, European businesses will invest between €2.4 and €3.3 billion in automation to boost productivity, including in lower-wage sectors.

 

Higher production and increased productivity are the two biggest advantages commonly attributed to automation. Other benefits related to automation are eliminating or reducing risks of human error on manual data entry tasks to ensure consistent quality in data entry. As businesses today collect enormous amounts of data, automation software can easily track all insights hidden in large portions of, often unused, data.

To start with automation, businesses must ask themselves, what are the goals they want to achieve with automation? Which process do they need to automate? Do they have automation tools and experts? What skills do their staff need to work in an automated environment?

 

Here below is a checklist you need to know before adding automation into your ecosystem:

 

    • Companies must know the goals that they want to achieve by implementing automation in their workflow. They can achieve their goals to make more profit, reduce overall operational costs or get the maximum work done in a minimum time, or efficiently utilize available resources and take appropriate strategic decisions. Once their goal and vision are clear, achieving results is easy and possible.

 

    • Once the goal is clear, the automation of necessary tasks must be number one on the priority list. At this point, the time, budget and human resources must be well calculated respecting the business process, also these three are the main resources and assets that can be saved once the automation process is placed.

 

    • Develop a roadmap that strategically focuses on investments that are needed to create a digital environment.

 

    • According to the Robotic Process Automation (RPA) annual report 2019 by Everest Group, the global independent RPA independent software vendor market surpassed US$1 billion in 2018, with over two-thirds of the revenue coming from software licenses. It shows the availability of so many automation tools that makes it harder to select the right tool a company needs to accomplish its goals. Therefore, they must choose the one which is easy to install by their IT specialist without any extern or vendor support.

 

    • Select and set up a team of employees that can implement smooth change management towards the digital workforce system instead of legacy software and create a continuous deployment plan.

 

    • Train IT managers to recognize opportunities to build and adapt the automation software to their needs and establish a modern technology environment to support the rapid development and adaptation of innovative solutions.

 

    • Companies that are newly introduced to automation tools/software, must keep in mind one of the most crucial factors for long-term survival, which are the running costs and licensing of tools, in addition to that make sure to opt for the tool that provides a smooth and secure data handling, as in automation processes, customer’s private or confidential information can be used.

 

    • Choose the software that will scale along with your automation efforts and provide for a full-scale digital transformation.

 

    • Pay attention to continuous improvement of critical business process planning and operations to develop a robust understanding of the business process and workflow and know what makes the processes tick and what doesn’t.

 

Once the automation strategy is placed, you can redeploy the human workforce to innovate and improve your business processes and deal with other priorities.

 

Sources :

CRM Automation: How can you elevate your Customer Relationship Management?

CRM Automation How can you elevate your Customer Relationship Management

The automation of companies has become a trend of our time. The modern market has set its own rules. The perfect product alone is no longer enough. In addition to the ideal product, customers also demand impeccable service. If a good product and competitive pricing are no longer enough to gain customers’ loyalty, then a personalized experience will have to be your differentiator. The competition is very strong, so a modern entrepreneur should pay close attention to customer management. Because one thing that 2021 has taught us, is to add good service to even the best product. Thus, automation is one of the most effective ways to effortlessly streamline your business.

 

The corona pandemic has further accelerated existing trends in automation. More and more companies want to automate their processes with the help of their CRM. The trend of collecting, unifying, and transforming customer data is becoming difficult and time-consuming without a proper data integration tool, but new offerings are finally making it possible for small and medium-sized businesses to do the same. One of the biggest benefits of automation is that instead of manually filling out all the documents, your team can let the software do it automatically. This gives them the opportunity to spend their valuable time on more important things. The software is programmed to work flawlessly, saving you a lot of problems and headaches and making the choice between tradition and automation obvious. CRM is becoming more and more synonymous with automation. The global CRM market is poised to reach about $113.46 billion by the end of 2027 (Globe Newswire, 2021).

 

As CRM takes care of a significant portion of the work processes; you don’t need to hire a big team to do the job but some entrepreneurs are still afraid to introduce the innovation because they are not sure if this solution really works and will be accepted by their team. Along with the fear of change, often companies don’t have an integrated approach to contact information and use different customer relationship management solutions that don’t communicate with each other. Without data integration tools, the process becomes difficult and time-consuming. In such a situation, employees need to log into multiple systems, download multiple sets of data to create their own unified customer database.

 
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On the other hand, the organizations which have successfully adapted to the new situation, use new tools and technologies to review and adapt their sales process to close more deals. Businesses that implement CRM automation experience an average of a 451% increase in qualified leads. (Annuitas Group). The CRM system, allows them to manage all contacted data of their customers and business partners in a structured and clear manner. They can record interactions and collect all important information about them along the customer journey, the journey from lead to purchase. Also, by bringing valuable data together, they are able to better understand and respond to the needs of their customers. Without electronic support, this mass of data cannot be handled at all.

 

Software for consolidating customer data easily connects disparate silos so data can be shared across systems for trend analysis, better decision-making, and greater customer satisfaction. For instance, using chatbots for communicating with customers, automating helpdesk tickets, or using automated email workflows to assist prospects in the sales process, customer management automation is on the rise. This automation enables companies to provide quality customer service while optimizing operational costs. The tools for this are also becoming easier and cheaper, which is why this is becoming more and more interesting, even for smaller companies.

 

However, it’s very important to choose software that is suitable for your team. Many CRMs look too mysterious but work as simple appointment schedulers. Therefore, the demand for quality software is very high among both small and medium-sized businesses. Well-designed software is user-friendly, which makes it easier for managers to explain the importance of the new software to their employees. It should definitely be done, and in this case, it’s not complicated.

A fully-integrated CRM system offers significant benefits but you must look for implementation options, scalability, adaptability, business value, and, of course, best value for money. The focus must always be on the individual requirements and needs of your company and the associated tasks, but also on employees who will use the system in the future.

Data: A key resource for Digital Business Models

Businesses are generating and collecting large amounts of data, due to the rapid digitalization in all sectors and industries. Digitization has come to stay so not only the volume but also the variety of data – structured and unstructured – is growing exponentially in companies around the globe. New sources of income and growth opportunities are what companies strive for today. The evaluation and analysis of data help significantly and are becoming more and more important for companies – because the results of such analysis are considered as a strategically valuable asset.

Data A key resource for Digital Business Models

Companies don’t just want to collect the data, but their goal is to get real benefit from it. The analysis of data, which arises from individual digital interactions, generates significant added value for companies. This also includes the processing of omnichannel data, regardless of whether they are structured or unstructured, to get better insights into the entire customer journey. In order to unlock this potential in companies, a data strategy is required, i.e. a plan for data value creation in the company. Because only those who use data in a targeted and intelligent way can make better and faster decisions, optimize processes, improve planning or develop new approaches, define new customer-specific offers, or even innovate the entire business model & define short- and long-term objectives.

If implemented correctly, a data strategy offers companies from all industries and, in all areas of the company, sustainable benefits. In the transformation process, management must take into account the data infrastructure, data management, the general data strategy approach, and data analysis and its use.

 

Data infrastructure

The development of future-proof and efficient data infrastructure is based on a high degree of flexibility in data generation, virtualization, and processing. For high-quality data analysis, companies should therefore increasingly focus on independent software components (microservices) that have interfaces with common communication standards and thus enable quick and flexible integration into new applications without detours. Particular attention should be paid to fast network architecture, the prevention of data silos (e.g. by introducing a data lake), and the inclusion of secure cloud solutions.

 

Data strategy

The development and implementation of a data strategy often present companies with challenges. A suitable data strategy must be adapted to an organization and its objectives. It defines how data is handled and which goals are pursued. Since data value creation is not just a technology issue, but rather affects almost all areas of the company as the core of digital transformation, uncoordinated and decentralized approaches often do not lead to success.

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Therefore, a correspondingly fast and agile strategy is required to achieve results quickly. If the decision is made on a static approach, the motto is usually “defense instead of attack”. The focus is clearly on strict regulations in the handling of data and data quality. With a strategic approach, companies choose the middle ground between strict guidelines and targeted data usage. Companies that take a dynamic approach to data handling use a large amount of data in order to be able to react quickly to market changes and to improve their own analytical skills. Fast data access and quick results are important here. In the dynamic approach, cost savings and profitability through the use of data come to the fore. Flexibility in analysis and quick availability of results, for example through user-friendly data visualization, is essential.

 

The data warehouse

No matter what you need your data for and how you ultimately create your data strategy, every modern organization with a lot of data needs modern data warehousing. The data warehouse is the universal place where data from many different sources is collected. If you are planning a suitable data strategy, the data warehouse is one of the most important core elements to be reviewed. In many companies, IT teams are looking for a suitable data strategy that simplifies administration and helps to draw value from all the existing data. A modern data warehouse must therefore be part of a successful data strategy. Companies working on a data strategy cannot avoid modernizing their data warehouse. And one of the most important tasks in this modernization is the automation of the data warehouse.

 

The goal of a strong data strategy should always be to build an organization where agility is an integral part of its DNA. Such an organization works with an operating model that focuses on the employee and the customer. The model equips the company with the ability to quickly recognize changing business requirements and to continuously develop. We support you in designing, implementing, and integrating data correctly into your existing system landscapes and thus into your processes. Feel free to reach out to our consultants that offer a wide range of business and technical know-how as well as the necessary instinct to solve the individual challenges of your organization. We can’t wait to help you find success.

 

 

Sources:

SAP White Paper: Digital Transformation – Digital Business Modeling A Structural Approach Toward Digital Transformation

Business Process Automation Trends 2021

As 2020 is slowly drawing to a close, it is time to discuss future trends in (industrial) automation that are likely to have a significant impact in 2021. Based on the current facts, conclusions can be drawn that artificial intelligence and automation will bring steady innovation for companies of all sizes and from all sectors. During 2020, automation technologies have experienced a substantial boom especially due to the covid19 pandemic. Industrial and manufacturing operations have been massively evolved with the integration of machine learning and robotics. In fact, companies and industries are no longer fully dependent on a human workforce for simple, complex, manual, and repetitive tasks. They are gaining a competitive advantage with digitalization and IoT.

Here below are the top emerging trends to watch in automation for upcoming years:

 

  • RPA and business workflows

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RPA isn’t new, many companies use this technology to automate their routine tasks. RPA as an industry is growing exponentially– the global robotic process automation market size is expected to reach USD 10.7 billion by 2027, expanding at a CAGR of 33.6% from 2020 to 2027 – Grand View Research. RPA used in the automation of manual and low-value repetitive tasks, such as data entry (order, invoice, etc), looking up information in databases, typing in updates, prepare a template, run and download reports, read and reply email, send emails to follow up with customers, etc. is passed. During the pandemic, organizations realized their technological backwardness and the risks associated with a further delay in digitization.

In 2021 everything will revolve around business workflows. The call for digital transformation is growing and ensuring streamlined, smooth processes that delight both customers and employees. To achieve this, companies are increasingly targeting intelligent RPA solutions. Because many processes in companies are still only partially automated – if at all. It will therefore be about making RPA technology even better usable in the future. With the integration of Cognitive RPA along with other intelligent components, business processes that require human reasoning or decision-making can be automated.  A robot cannot, therefore, decide on its own to add a new dimension to the process that has not been precisely defined before. This is the only way to automate business-critical workflows end-to-end, for example.

 

  • Automation and Cyber-Threat

In order to protect against automated modern cyberattacks, organizations will be incorporating automation into cybersecurity efforts. Automation plays an important role in defense against threats. Modern automatisms will increasingly develop their effect in the fight against the threat by reducing the volume of threats and allowing faster prevention of new and previously unknown threats.

If implemented appropriately, providers of cloud platforms can take action against cybercriminal groups that use trusted services for malicious attacks. In the past, it has been observed how legitimate websites – for example, Microsoft365 or Google Drive – have been imitated in order to steal data entered by unsuspecting victims. With the right tools and validation technologies, automation can aid in the prevention of successful cyberattacks and track down such fake login pages – with the aim of counteracting the risk.

 

  • Digital employees

As the ongoing global pandemic, has triggered an acceleration of a digital working environment, business leaders are learning lessons to apply to their futuristic organizations. Remote work is here to stay; thus, many organizations were forced to tap into their technologies and pushed creative ways of leveraging them to ensure business continuity. Businesses around the globe are exploring how they can implement and strengthen their digital strategies and unleash the true power of Technology – not just from a technology and environment perspective but from leadership, change management, and career-growth perspectives, as well. Companies are preparing themselves for the hybrid future or work by investing heavily in the tools needed to work remotely and prioritizing tech and digital infrastructure investments that support sustainable remote/hybrid work.

While no one knows exactly what the future holds for us, according to Forrester, companies are investing a lot in an “anywhere-plus-office hybrid” model in which more people will work outside the office more of the time. Therefore, it’s certain that remote working will play a major role in how the workplace will evolve in the coming years and will continue changing the way we work.

 

Sources:

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