In this era of big data and analytics, it has become important for organizations to have an access to timely and transparent data that can add value to their processes. Any data, if utilized and channelized effectively, can solve various complex issues, optimize processes, and enable making sound decisions. A leading company, Innovu was founded on the belief that by bringing together vast silos of data in the human capital continuum world, it can unlock powerful knowledge to solve complex challenges.
Innovu pours through claims information from payers in order to help the self-funded advisors and employers gain better insights about why those costs have been escalating at double-digit rates over the last 10 years. Its analytics platform helps to uncover where there’s an opportunity to help eliminate waste and manage that risk better. It also enables the advisors that work with self-funded employers to put in the appropriate solutions to then reduce that cost. Innovu focuses on three major continuums which includes healthcare spend, workers’ compensation risk, and retirement sectors. Its vision is to continually add different data sets and provide unique solutions using analytics to allow the advisors to help their employers while lowering their cost.
Delivering Appropriate Solutions
Innovu securely, accurately, and seamlessly integrates data across all programs to create a consolidated “single truth” of information. The part of its core functionality is to use machine learning to match members into the platform so that individuals can do analysis across the different sectors such as healthcare, workers’ compensation, and retirement. The company is training its machine to continually match people because, depending on what system it comes from, they’ll have missing information, incomplete, or wrong information. This is one of the core technologies that the company is leveraging. Kevin states “It’s really about leveraging analytics and comparable analytics to benchmark where one employer might have a higher spend than others. And so, it’s really about the comparative analytics and the ROI, the prospective looking analytics that we apply to the data to bring that value out.” “29 and a half percent of the time, the data that we collect is incomplete, missing, or wrong, and so we’re enhancing the data in our platform by filling in those critical elements, so that employers can gain better insight into their healthcare spend, and advisors can implement the appropriate solutions, to realize actual savings and RIO” he adds.
An Industry Veteran
Innovu is led by veteran entrepreneurs, benefits and risk experts, and technologists who provide agile solutions that empower clients to integrate their data to gain valuable insight to make more strategic business decisions. One member of its core team is Kevin O’ Brien, the Senior Vice President of Distribution of the company. Kevin was also Innovu’s first customer. So, his background is actually on the insurance advisor side. He has spent 15 years with a large regional advisor in Pittsburgh. He brings an industry experience of how advisors are using data to uncover opportunities with their clients and how Innovu’s product can fill those needs in the company. Also using his knowledge and contacts, he has contributed to build out the distribution team nationally. His expertise positions him to leverage the company’s technology platform and service model to provide actionable insight into how clients can lower their total cost of human capital.
A single source of truth is a central and controlled source of data from which the entire organization can draw.
It is the master data.
When you lack such data and employee can pull down apparently the same metrics from disperse systems, unavoidably those systems will produce different numbers.
You get into a he-said-she-said situation, each player drawing and defending their position with their version of the ‘truth’.
Or even worse, some teams may naively leverage stale, low-quality, or otherwise incorrect data/metrics and make bad decisions, when they could have leveraged a better source.
In general, business that give way for the inclination of digital transformation therein achieves greater control over its processes, and with high flexibility offered across IT Systems, a lot of digital transformation companies can now any time move ahead to build the smart strategy to stay ahead in the competition.However, the infinite proliferation of new technologies has resulted in inducing both the software development companies and software engineers to believe that these applications would soon have an update and therefore take up a heedless approach towards it.
A research study conducted by IDC, states that 67% of Global 2000 Enterprises might build the most suitable digital technology solutions and develop a resilient business strategy by this millennium.Legacy Applications are a major requirement when it comes to Automating a business.
In this blog, we have discussed the importance of legacy applications for automation.Learn more at Legacy Applications in Data-Driven Industry.
The socio-economic fallout of the pandemic and geopolitical unrest continues to test the resilience of business models and resolve of the functional leaders.
HBR reports that 91% of the insiders acknowledge the centrality of data and analytics to successful business transformation.
It implores CIOs, innovation leaders, and CDOs to collaborate and embrace a data-first culture, uncovering new opportunities for creating exponential business values.The OECD defines DDI as applying data and analytics to elevate product development, business processes, organizational methods, or go-to-market (GTM) strategies.
Some such use cases can be:Product development: Data and analytics help identify gaps in the concepts and prototypes and point towards possible product and service innovation opportunities.
Also, Intuit monetized the usage data of its personal finance management (PFM) tool Quicken to seek out improved business opportunities, developing the QuickBooks accounting package for SMEs.Business decisions: Over 90% of the businesses that prioritize data and analytics in their decision-making culture feel confident about assuming faster and relevant choices.
The OTT platform arrived at a conclusion by correlating customer behavior data sets around the popularity of the lead actor, the director, and the original British TV show.
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