How a Smart Data Analytics Strategy Can Help Businesses in the New Reality
– by Ilian Georgiev, Service Delivery Manager at BRIGHT
We spent a year in uncertainty but what is certain is that companies cannot stand still and wait for the storm to pass.
What we learned from 2020 is that businesses should be awake and take advantages of innovative technologies to stay competitive. Organizations should rethink their data analytics strategy and adopt solutions that increase efficiency and productivity.
What are the main technology advantages today?
The following areas reveal the power of data and the potential of new technologies in business analytics:
Real-time monitoring and alerting – The ability to track the pulse of the business
Organizations have already realized how much data they have. This data often becomes a liability due to very sophisticated processes of using it. How can we turn our data into an asset? Many organizations have switched to platforms and solutions focused on the data that produces value. Their goal is to provide fully automated real-time monitoring, analysis and forecasting of the business dynamics. Having this, the data is turned into action and used immediately when available.
Data storytelling – The ability to communicate with data
It is important for the analytical platform to send personalized, automatic notifications when an event (for example an issue) occurs. Often, during the root cause analysis, a set of routine tasks is performed. It is essential to highlight events and provide the business with a predefined routine analysis, diagnosing the state. Thus, the business could be a few steps ahead, increasing efficiency and productivity. That is what we call “data storytelling.”
Automated machine learning – The ability to use the full potential of data
Previously, the development of Machine Learning solutions was a time-consuming and expensive process, requiring niche experts. From a technology used primarily in multi-billion companies, today, AI has become more accessible.
What is most impressive are the Artificial Intelligence solutions, providing full automation of machine learning models (MLOps). These AI platforms give highly accurate forecasts and shorten the journey from data to value. DataRobot, the leader in Automated Machine Learning, is one of the most outstanding examples.
The machine learning solutions could answer many questions like:
- How can R&D identify the best materials?
- How can a factory eliminate defects?
- How can logistics predict container filling volume?
- How can a business predict the future demand?
- How can operations eliminate fraud? and many more.
Is there a link between technology, data analytics solutions, and business processes?
To take advantage of innovation, an organization must create an environment that allows it. It is necessary to create a culture that encourages change and improvement. Technology and business should complement each other. Technologies must be in line with business processes to achieve high efficiency and return on investment.
However, there is no doubt about technology’s ability to highlight opportunities for business process improvements and stimulate change. Experience has shown that solving a problem can open our eyes to hidden challenges we do not know existed. And this is the natural path to success.
How far can we go?
In today’s dynamic market, business decisions need to be made faster than ever. There are almost no limits as to how far we can go, but what is becoming the “new normal” in technology are the real-time monitoring, alerting and machine learning platforms that could:
- Automate and accelerate the routine operations.
- Give the power of data science in the hands of the business experts.
Having a significant technology toolset, experts with real potential and goal-oriented attitude could focus on business growth instead of performing repetitive, routine tasks. Thus, expanding the scale of the business will become a natural process. Experts will drive growth instead of being pushed by the management.
What is the price of Automated Machine Learning solutions?
Each investment has ROI – this is the way to approach any technology implementation. AI and automated machine learning solutions have the potential for a three-digit ROI and could be delivered in a fraction of the time.
What is the most important in building Automated Machine Learning solutions?
The teams’ ability to understand business goals and acquire subject matter expertise fast is an essential success factor. Here is an example of how BRIGHT helped Bulgaria’s market leader in logistics – Econt, optimize its capacity, utilizing the power of ML.
If you are looking to improve and streamline your data analytics strategy, our team will be happy to connect and share experience around your data-driven initiatives.
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