Tag Archives: AI

Data Management Guide for small business

A Data Management Guide for Midsize Companies

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The ability to track, extract, and analyse data on an enterprise-wide scale provides a strategic advantage to midsize businesses. With effective data management, these companies can mine in-depth insights to drive customer engagement as well as optimize costs and workflows.

Big data management entails tapping into in-memory processing, which enables applications to access and manipulate data very fast as it’s generated.

Armed with in-process business intelligence, operations personnel can make better, informed choices. Leveraging these data insights can also help improve employee/customer engagement.

Here are the basics for leveraging enterprise data for predictive analytics and decision making.

Use Appropriate Data Structures

A sizeable chunk of your data will be streaming in unstructured from diverse sources, and you’ll need a way to structure it for analytics as well as querying applications. As such, think about how you intend to use the data, and figure out a way to sort, tag, or classify it.
If you don’t have the necessary big data mining tools and AI analytics resources to extract, organize, and study massive amounts of unstructured enterprise data, consider engaging a provider who can help.

READ NOW: How High-Tech Companies Are Pioneering The Digital Economy

Connect to the Internet of Things (IoT)

You haven’t yet figured out everything there’s to know about how customers are using your product or service if you’re not leveraging the enterprise IoT. Connecting the technology to products enables companies to monitor, gather, filter, and scrutinize usage, performance, or platform data using AI or machine learning applications.
IoT data analytics can help an organization make mission-critical, operational, technology, or business decisions. The technology delivers big data that’s virtually impossible to track, collect, and analyse in real time using traditional techniques.

Build the Capacity to Process and Store Big Data

As your digital footprint expands, you’ll be generating or receiving massive chunks of enterprise data rapidly. Do you have the physical infrastructure required to store it in-house?
As a midsize business with potential for growth, you may prefer to invest in cloud storage. This way, you don’t have to spend heavily on redundant storage capacity. You can scale gradually in tandem with the rising volume of business data.
Cloud storage allows you to employ big data analytics while on the move, including using mobile devices. It enables your employees to make data-driven decisions on demand, regardless of their physical location.

Invest in Big Data Transmission and Processing Capacity

Be sure you have sufficient bandwidth to accommodate the rapid flow of massive chunks of enterprise data. The need to access and analyse some of the data in real time makes it paramount to deploy adequate network and processing capacities. Equally important, don’t forget to make technical provisions for any CPU-intensive big data-mining, AI, or ML applications.

Secure Your Enterprise Data

Some of the data you’re collecting or storing constitutes sensitive personal information or business secrets. You need to secure it in compliance with relevant local and international regulations. There are costly legal and financial ramifications for not complying with cybersecurity laws.
If you have business data in the cloud, be sure to figure out who between you and your provider is legally responsible for its protection at rest and in transit. Typically, encryption, multi-factor authentication, firewalls, and anti-malware are critical cybersecurity measures you need to have in place.

Summing it Up

Leveraging data analytics can help midsize businesses boost productivity, streamline workflows, and register incremental revenues. Fortunately, they don’t have to deploy costly on-premises infrastructure to do that.

Instead, the companies may partner with strategic cloud providers to help optimizing enterprise data management to drive business value.

For more information on how to leverage Big Data to grow your business call us on 1300 045 046 or email [email protected].

ERP of the Future- 2018 Top Trends in Enterprise Resource Planning

ERP of the Future: 2018 Top Trends in Enterprise Resource Planning

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Enterprise Resource Planning has evolved appreciably over the past decade or so. It’s very advanced today, and it continues to grow into a versatile, scalable, and multi-faceted resource that businesses of all sizes may leverage to catalyze performance enhancements in the value chain.

Our predictions for the top ERP trends to track going forward

After having implemented ERP software for small and medium-sized businesses for over a decade, we believe that the top innovations will come in the following areas.

#1 – The Internet of Things (IoT)

IoT is the digital connection or networking of otherwise independent devices or systems, such as cars, assembly lines, and electrical equipment. By feeding real-time data on product usage, performance, or technical problems into a centralized ERP database, IoT provides the insights required to improve quality, streamline production processes and lower costs, customize the customer experience, or manage logistics more efficiently.

IoT lends itself to various outcome-oriented service models. In consumption-based insurance, for instance, the provider uses vehicle-installed software to track mileage and monitor their customers’ driving habits. The system sends the information to the insurer’s business management solution autonomously, enabling them to calculate monthly car-insurance premiums for a customer based on usage and risk assessment.

#2 – Software-as-a-Service ERP

Many businesses are no longer finding in-house legacy ERP financially or operationally tenable. They’re progressively shifting to SaaS ERP to reduce the total cost of ownership (TCO). The approach eliminates the bulk of capital injections associated with acquiring major tech solutions for business.

SaaS enables companies to deliver a host of ERP applications to end users, such as employees and suppliers, via the cloud. It provides access to data and user interfaces or portals through any internet-connected device. With the ability to work from any location with internet access, employees can build greater adaptability and responsiveness to dynamic demands of their official positions.

The model allows companies to scale, upgrade, and switch between applications without investing in new hardware. They may introduce new software to the mix as needed, including CRM, talent management, or inventory control, and still, keep the benefits of cloud ERP integration.

#3 – Artificial Intelligence (AI) and Machine Learning (ML)

Through machine learning, ERP solutions can become smarter to the point of predicting future business opportunities and risks without human intervention or explicit programming. For example, ML algorithms may incorporate real-time data from various internal and external sources, enabling organizations to work out production costs and avoid setting loss-making prices for their products.

AI will play a critical role in enabling ERP solutions to make decisions autonomously. It’ll reduce human intervention to just passive supervision, allowing decision-makers to commit more time to value-added workflows.

To make it work, an intelligent ERP first records user input and the ensuing sequence of actions. Its built-in ML capabilities enable it to draw from historical data and to provide viable recommendations. With time, the system learns to make the right call every time without user input.

#4 – Big Data

Primarily, ERP utilizes a centralized database to support a broad spectrum of business functions. However, companies need much more than structured data to understand their markets, personnel, and customers better. Big data analytics helps these organizations decipher the sheer chunks of structured and unstructured data flowing in very fast from both internal and external sources.

For instance, in customer relationship management, big data enables marketers to extract and analyze data from sources such as social media, contact centres, and sales to enhance customer service, predict demand trends, and calculate ROI on several marketing initiatives.

ERP with Big Data capabilities can also help recruiters with talent acquisition and management. Such a system extracts invaluable job market insights from job boards, social media, and HR systems, enabling employers to meet their staffing needs.

Is your organization well-positioned to leverage ERP systems of the future? Powered by ML algorithms, AI, and IoT, the business management solutions are getting smarter and more versatile. Talk to us today about implementing best in class ERP software for your business!