4 items tagged "automation"

  • How automated data analytics can improve performance

    How automated data analytics can improve performance

    Data, data, data. Something very valuable to brands. They need it in order to make informed decisions and in the long term, make their brand grow. That part is probably common knowledge, right? What you are probably wondering is how big brands are choosing and using the right data analytics that will bring results. Find out the answer to that question here.

    Data analytics to learn more about brand performance

    More and more companies are investing in brand. The problem is that they don’t know if their investment is bringing results or not. Of course they can work off their gut feeling or some numbers here and there from Google Analytics or the like, but what does that really tell them about the impact of their brand campaigns? Not much. That’s why big brands are using MRP-based data analytics coming from brand tracking. They are using the precise and reliable data that advanced data science can bring them in order to make sure the decisions they make are indeed based on fact.

    Data analytics for risk management

    Following on from the last point of big brands needing precise data to make informed decisions, they also need such data for risk management. Being able to grow as a brand is not just about knowing who their customers are, their intention to buy their product, etc., it is also about being able to foresee any potential risks and knocking them out of the park before they can cause any damage. Take for instance UOB bank in Singapore, who have devised a risk management system based on big data.

    Data analytics to predict consumer behavior

    As much as big brands need to look into the future, they also need to look to the past. Historical data can do wonders for future growth. Data analytics can be used to pinpoint patterns in consumer behavior. Using the data, they can potentially predict when a certain market may take a nosedive, as well as markets on an upward trend that are worth investing money into right now.

    Data analytics for better marketing

    A combination of data analytics looking at the past, present, and future of a big brand can make for better marketing, and in turn, more profit. By using data analytics to identify consumer needs and purchasing patterns, big brands can target with more personalized marketing, refine the overall consumer experience, and develop better products. Pay attention in your everyday life and you can already see examples of such data being used to market a product at you. A product you Googled once now appearing in your Facebook feed? Retargeting. Emails sounding like they are speaking directly to your needs? That’s because they are, since there are more than a few email marketing approaches. Data analytics was used to figure out exactly what you need.

    There is one important trend occurring across the different ways that big brands are using data analytics to bring results. They all aim to understand consumers, in particular, the brands’ target audience. Whether that be what consumers think of their brand now, how they reacted toward them in the past, and how brands think consumers will act in the future because of detected patterns.

    So, how are big brands using data analytics that will bring results? They are using them in a way that will help them better understand the consumer. 

    Author: Steve Habazin

    Source: Insidebigdata

  • How businesses can support citizen developers towards success

    How businesses can support citizen developers towards success

    It is estimated that by 2030, there could be a shortage of 10 million developers in the U.S., according to Forrester Research. This shortcoming, coupled with the proliferation of automation tools, is sprouting an army of citizen developers: professionals who aren't trained in computer science but are becoming de facto programmers through the influx software available to them.

    While some employees eagerly jump at the opportunity to become citizen developers, others have held back from embracing this title, notes Justin Donato, vice president of information technology at Nintex.

    Heading into 2020, which is primed to be the automation decade, enterprises need to work to qualm employee anxieties (job security, ageism, bandwidth, etc.) associated with becoming a citizen developer, Donato says. Information Management spoke with Donato about the growing need for citizen developers and how organizations can build a culture that fosters citizen developers.

    Information Management: How can enterprises build a culture that encourages citizen developers?

    Justin Donato: The most important things enterprises can do to encourage citizen developers are to give them the right tools and empower them to use those tools within a data culture. One of the major success criteria for a citizen developer is a no-code solution. Unfortunately, in many organizations, IT departments keep these solutions from the business or citizen developer types.


    IM: What will citizen developers look like in the next year? Can anyone be a citizen developer?

    Donato: Citizen developers are on the rise. Anyone in the organization who really understands a process and how it works is a great candidate to build and manage their own solutions. Typically they start with a system of record like SharePoint, Salesforce or other repository of data and quickly start automating processes around those systems.


    IM: How can employers ease employee anxieties often connected to the rise of automation?

    Donato: In a wide variety of scenarios, automation is making processes much more efficient and accurate. Employers are seeing that the employees involved in these processes are reducing inefficiency and adding more value.

    Smart managers are recognizing and rewarding employees for automating processes that help the business run better. Those employees are being great stewards of the company time and resources that they have been entrusted with.


    IM: What are the key steps in implementing a successful automation strategy?

    Donato: Executive support is often the key to driving success. I personally have found it very helpful to have a tool that allows me to start by documenting the process I want to automate.

    Keep that documentation up to date and leverage it as the foundation for the next step, the actual automation. This provides a great working copy of processes that you are automating.

    On the automation side, giving citizen developers no-code solutions that are fast and easy to use is the key to long-term sustainability.

    Author: David Weldon

    Source: Information Management

  • Intelligence, automation, or intelligent automation?

    Intelligence, automation, or intelligent automation?

    There is a lot of excitement about artificial intelligence (AI), and also a lot of fear. Let’s set aside the potential for robots to take over the world for the moment and focus on more realistic fears. There is a growing acceptance that AI will change the way we work. There is also agreement that it is likely to result in a number of jobs disappearing or being replaced by AI systems, and others appearing.

    This has fueled the discussion on the ethics around intelligence, especially AI. Thoughtful commentators note that it is unwise to separate the two. Some have suggested frameworks for the ethical development of AI. Underpinning ethical discussion, however, is a question of what AI will be used for exactly. It is hard to develop an ethics framework out of the blue. In this blog, this issue will be unpicked a little, sharing thoughts about where and how AI is used and how this will affect the value that businesses obtain from AI.

    Defining intelligence

    Artfiicial Intelligence has been defined as the ability of a system to interpret data, learn from it, and then use what it has learnt to adapt and therefore achieve particular tasks. There are therefore three elements to AI:

    1. The system has to correctly interpret data and draw the right conclusions.

    2. It must be able to learn from its interpretation.

    3. It must then be able to use what it has learnt to achieve a task. Simply being able to learn or, indeed, to interpret data or perform a task is not enough to make a system AI-based.

    As consumers, most of our contact with AI is with systems like Alexa and Siri. These are definitely "intelligent," in that they take in what we say, interpret it, learn from experience and perform tasks correctly as a result. However, in business, there is general acceptance that much of the real value from AI will come from automation. In other words, AI will be used to mimic or replace human actions. This is now becoming known as 'intelligent automation'.

    Where does intelligent start and automation stop though? There are plenty of tasks that can be automated simply and easily, without any need for an intelligent system. A lot of the time the ability to automate tasks is overshadowing the need for intelligence to drive the automation. This typically results in very well-integrated systems, which often have decision-making capabilities. However, the quality of those decisions is often ignored.

    Good AI algorithms can suggest extremely good options for decisions. Ignoring this limits the value that companies can get out of their investments in AI. Equally, failing to consider whether the quality of the decision is good enough can lead to poor decisions being made. This undermines trust in the algorithm. This results in less use for decisions, again reducing the value. But how can you assess and ensure the quality of the decisions made or recommended by the algorithm?

    Balancing automation and intelligence

    An ideal AI deployment should have a balance between automation and intelligence. If you lean too much towards the automation side and rely on simple rules-based automation, all you will be able to do is collect all the low-hanging fruit in this case. You will therefore miss out on the potential to use the AI system to support more sophisticated decision making. Lean too much towards other direction though, and you get intelligence without automation or systems like Alexa and Siri. Useful for consumers, but not so much for businesses.

    In business, analytics needs to be at the heart of an AI system. The true measure of a successful AI deployment lies in being able to mimic both human action and human decision making.

    An AI deployment has a huge range of components, it would not be unreasonable to describe it as an ecosystem. This ecosystem might contain audio-visual interpretation functions, multisystem and/or multichannel integration, and human-computer interface components. However, none of those would mean anything without the analytical brain at the centre. Without that, the rest of the ecosystem is simply a lifeless body. It needs the analytics component to provide direction and interpretation of the world around it.

    Author: Yigit Karabag

    Source: SAS

  • Why you should implement automation in your business

    Why you should implement automation in your business

    When automation is done well, it accomplishes more than just saving time and money. It minimizes errors, improves productivity, increases employee satisfaction, and enhances the customer experience. When incorporated into a business strategy, employees get more done, in the same amount of time, allowing them to focus on the important objectives of their role.

    While automation may not be the latest advancement in technology, it will have the greatest impact on how we do business over the next decade. IT managers who fail to employ automation will likely lose their competitive advantage. Gartner estimates a 25-percent reduction in customer retention over the next year for companies that choose not to incorporateautomation into their business strategy.

    What is automation and why do it?

    Automation enables the workflow to proceed without human oversight. Automation can be deployed in place of traditional manual systems such as entering purchase orders, customer service, data analysis, and reporting. Eventually, nearly all IT teams will automate some aspects of their businesses. As businesses grow, automation will expand customer service without increasing the number of employees. Successful automation enables your existing teams to manage additional customers with the same speed of service. Simply put, automation allows the company to accomplish more with less.

    Automation benefits both the company and its customers. Customers report an improved experience due to better consistency in order fulfilment, faster response times, and lowered costs. Improved customer experience will improve brand loyalty and increase customer lifetime value. Automation empowers companies to optimize the way they allocate internal resources to save money, and take advantage of new opportunities to increase sales. In other words, businesses are either saving or earning money when they automate.

    Reporting

    Automated reporting comes as part of the package with BI solutions. Users can access relevant and timely data on how the business is performing across all domains. By instantly converting raw data into actionable information, automated reporting eliminates the challenges associated with traditional forms of reporting. Now users can see what has happened, what is happening, and what is likely to happen in the future.

    Reports can be generated automatically at set times, such as every monday morning for the weekly sales meeting. Reports also may be triggered by certain events, such as when sales figures fall within a certain range. Self-service analytics also provides users with a customizable dashboard for on-demand reporting based on job role. A dashboard allows users to see what is happening in real-time, and to drill down into the details to see the root cause of problems, as well as to identify new trends and opportunities. From sales teams to inventory managers, users have access to up-to-the-moment data from anywhere, on any device.

    Security

    The cloud offers cost savings as well as added security benefits. IT managers and CTOs work with the SaaS providers to determine the level of access to be provided to users in their business. They can determine when devices should be able to access resources and restrict permissions to users based on their job roles. Security should be a priority. Both in private cloud and dedicated SaaS, it is important to manage and minimize data breaches the best way possible. To ensure the ongoing security of customer data, independent regular vulnerability and penetration testing and having a security incident response policy in place is recommended.

    When companies embrace automation, employees have time to work on items that add genuine value to the business, allowing them to be more innovative and increase levels of motivation. Customers also benefit from improved service and experience.

    Source: Phocas Software

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