Nowadays, big data and analytics is on the top of the corporate agenda. It helps the businesses to make sense of structured and unstructured data and applies that knowledge to enable insights, innovation, and improved decision making across a wide range of business functions. If your organization doesn’t have the skill—and the will—to use this data, wasting resources in collecting such data is ludicrous. It is absolutely essential to build a data-driven culture in your organization that can make analytics projects truly pay off.
With technology being the most fundamental aspect of every business, you can use the data it generates to see exactly what’s happening in your organization and the world around. You can then use that information to make your business more Agile by testing out different scenarios and their success. You don’t necessarily have to be a data scientist to reap the rewards. Here are some simple steps to follow for more data-driven business decisions:
Select the right useful data
We may not be aware of the “unbelievable” amount of data we push onto web each day. The “unbelievable” number of around 2.5 quintillion bytes —that’s a 1 with 18 zeros after it—is published by IBM in their Watson Marketing journal.
How do you know you’re selecting the right data samples to investigate? Big data is a heavy quantitative term and hence, the moment one talks about big data, it expresses huge volumes. These volumes of information are growing rapidly, while opportunities to expand insights by combining data are accelerating. Bigger and better data give companies more comprehensive, yet grainy, views of their business environment. Data is the central piece of predictive analysis. If you have the right data, and investigate the right parameters, your models and predictions will be accurate.
Source data creatively
Creativity and data-sourcing go hand-in-hand. One needs to get creative about the potential of external and new sources of data. But to come up with an idea that people will like, share, discuss and debate is quite challenging. It still takes messy yet sharp, insecure yet inquisitive human mind to reap insightful data, find potential and ultimately turn all that data into business. One way to prompt mindfulness about potential data is by questioning, “What decisions could we make if we had all the information we need?”
A reliable IT Support is must
The conventional IT structures, running with certain legacy, may delay in conferring new types of data sourcing, storage, and analysis. Every so often, managing unstructured data remains beyond traditional IT capabilities, while existing IT architectures may prevent the integration of layered information into existing systems.
With great opportunities of big data in bringing real business value, comes great challenges of analyzing it. Addressing the big data management issues is not enough, people are now looking forward towards integrating big data analytics software to identify trends, detect disruptions and glean other valuable findings from the resourceful information available to them. Building a big data analytics application is baseless without an IT support. You’ll need an impeccable IT support to address the volume, velocity and variety of data.
Build models that predict and optimize business outcomes
Businesses, governments, and leading organizations need to rely on a good predictive analysis model, not only to survive, but also to thrive in the current economic climate. A consistent model allows an organization to predict consequences and then proactively act upon that vision to drive better business outcomes and achieve the competitive edge.
Such analytics model helps businesses to connect data and an effective action by drawing reliable conclusions about present conditions and future events. Data is an essential element, but performance improvements arise from analytics models that allow businesses to predict and optimize outcomes.
Unquestionably, advanced statistical methods always make for better models. However, sometimes statistics experts design too complex and impractical models, which may exhaust most organizations’ capabilities. Hence, it is necessary that we focus on the least complex model to incorporate in our business.
Transforming your company’s capabilities to align
There’s a certain mismatch between organization’s existing culture and capabilities and emerging tactics to exploit big data analytics successfully. This often leads to organizational failure in reaping the benefits of big data analytics. The new methods either don’t align with how companies actually arrive at decisions or fail to provide a clear outline for realizing business goals. Using big data requires thoughtful organizational change, and the following areas of action can get you there:
- Build a data-driven culture
- Develop business-relevant analytics that can be put to use
- Establish analytics in simple tools for the front lines
- Develop capabilities to exploit big data
Even with simple and usable models, most organizations will need to upgrade their analytical skills and literacy. Efforts will differ, depending on a company’s goals and desired time line. Fine-tuning cultures and mind-sets typically requires a multi-layered approach that includes role modeling by leaders, training for new technologies, and incentives and metrics to reinforce behavior.
Conclusively, at the very first, companies must be able to identify, combine, and manage multiple sources of data. Secondly, they need the competence to build advanced-analytics models for predicting and optimizing outcomes. Third, and most critical, management must keep the influence to transform the organization so that the data and models yield better decisions. A clear strategy for using data and analytics to compete and the deployment of the right technology architecture and capabilities are the two most important features that underpin the above competencies.