As a consequence of the global pandemic, there’s arguably never been a greater focus on the value of high quality, real-time data. As governments plot their roadmaps to recovery, it’s data that is informing the big decisions from vaccination strategies to the re-opening of shops, services and public transportation.
At KX, we’ve long understood the key role data plays in making critical business decisions. Magic really does happen when you combine historic and real-time data to deliver actionable insights for business decision making when they count the most.
Research commissioned at the beginning of the year validates this perspective, with 90 percent of companies reporting they intend to boost investment in real-time analytics services during the next three to five decades. Moreover, almost two-thirds (64 percent ) of businesses think that getting access to real time data is essential to making smarter business decisions, while over three-quarters (78 percent ) say real time data and insights are developing a competitive edge for their organization.
However, the study also demonstrates that companies may be missing out on pulling the complete value from their information by not thinking quickly enough in regards to real time decision making. Research demonstrated that 69 percent of companies believe real-time to mean within per moment, with 45 percent of the category specifying real time as anything upward from one hour.
Irrespective of business — finance, production, utilities, telecommunications, and many others — requiring decisions from moments to microseconds could be a game changer for them.
According to our experience working with all these companies, we consider there are five steps for carrying real-time analytics into a sub-second level and empowering an operating version of constant intelligence.
1. Assess and understand
While not all companies will need to be working at the sub-second level, all companies create data in real time, and also an understanding of where and how faster analysis could result in better operational and industrial performance is obviously helpful. Firms should ask themselves the following questions.
Is there a thorough comprehension of the worth of the information that flows inside a company and seriously, the pace at which value declines once created?
- Can there be data-led civilization and are the right tools and procedures in place to guarantee the people and software that could extract whole value from this information set up?
- What will be the expectations and intentions placed against investments in real time information analytics technology and how can success be measured?
There’s broad agreement about the value that an investment in those transformative technologies can contribute to a company. Equally, access to the ideal technology and having the ideal people with the appropriate skills are typical challenges. Possessing a clear understanding upfront of this information landscape, culture and goals is critical.
Also read: 14 Ways To Create A Highly Efficient Software Team For Your Startup
2. Get your data in shape
To put it differently, the better a firm’s understanding of where the information resides, its structure, and its own history, the better positioned they will be to reevaluate the decision-making window. Below are the most frequent forms of datasets that companies often attempt to attract together. Each is a different, different set and the association between them may be complicated.
- Datasets generated internally
- Datasets sourced externally
- Streaming data
- Data at rest
- Structured data
- Unstructured data
It’s very important to recognize that a few info and data sources are more precious than others. Time series data, by way of instance, is among the most valuable resources, especially when created in the IoT marketplace. Highly structured, machine-generated, and delivered with timestamps between several thousands of devices at very substantial frequencies, it’s relatively new to the majority of organizations but precious. And you want a complete strategic option to using it well.
3. Think faster
Once a robust, core real time analytics strategy is set up, challenge the team to think faster by learning and testing.
The very best real time data systems allow sandbox environments where information scientists can construct models and test results quickly without the stress of affecting essential systems operating in parallel. Here is the bedrock for unearthing news tips that enable the pragmatic development of new capacities, always adding value as time passes.
4. Anticipate challenges
The principal data challenge – and opportunity – which many businesses face is no more that of quantity, but of rate. Streaming analytics solutions will need to operate with new and existing datasets and so, need to interact with numerous existing engineering. Afterward, interoperability could be challenging.
Also, IT teams may be modest, elongated, or just battling for the perfect gift in an increasingly competitive environment. Implementing a new technology may be an overwhelming job. But in addition, it presents a chance to upskill the workforce in regions that are going to be vital to your business’s future success.
5. Find the right partner
Once the choice is made to increase investment in real time analytics, the next step is to locate the right spouse. There are many questions to consider when doing so, for example:
Ask about a typical engagement. Streaming analytics extends beyond getting data to document quarterly meetings. Always search for a supplier with clear and demonstrable expertise in assisting companies to create those sub-second decisions.
Ask about iteration and future flexibility. Since innovative, streaming analytics is a growing area, your supplier should be able to clearly demonstrate how they intend to keep adding value as time passes. That may, of course, imply iterating their answer and supplying regular updates and updates to match market requirements.
Look for a partner not a provider. Businesses benefit from technology when sellers think past the initial purchase. And in addition, organizations should be looking for a collaborative, strategic spouse through time, instead of a one-time purchase.
Analyzing data is a procedure we can’t ignore, especially today because it educates significant nationwide decision-making. The possibility of flowing analytics is enormous. But only in case you’re able to think fast. A microsecond mindset is essential to equip your company with the resources required for faster, smarter, and more precise decision making. Finally, resulting in a competitive advantage the business never had before.
Leave a comment