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How Can You Measure Employee Engagement?

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Employee engagement is one of the most important metrics for the success of an organization, but it’s an elusive figure. According to one recent Gallup poll, a meager 15 percent of employees define themselves as “engaged” with their work. But what does that really mean? And how can you measure or improve employee engagement in your organization?

What Is Employee Engagement?

Employee engagement is a nebulous term, so you might get a different definition for it depending on who you ask. However, for the purposes of this article, you can consider employee engagement as a level of connection an employee has to the work they do on a regular basis and a sense of loyalty to their employer. The more engaged an employee is, the more productive they’re going to be, the more likely they’ll be to stay with an employer, and the more fulfilled they’ll feel, subjectively.

Additionally, keeping employee engagement high can be good for your reputation as an employer.

Boosting employee engagement can take many forms. For example, you can use digital signage to provide motivation to employees, or to publicly recognize employees who have accomplished something great. You can also improve engagement by promoting high-performing employees to higher positions, and by making your work culture more interesting or desirable.

The trouble is, what engages one employee may not necessarily engage another, and some strategies will naturally be more effective than others. How can you tell which strategies are most effective, or which ones are working at all?

How to Measure Employee Engagement

There are a few different ways to measure employee engagement, though each area has weaknesses:

  • Direct surveys. You could simply ask your employees whether they feel engaged. Here, there are a few potential approaches. For example, you could send out a survey once a month that asks employees how engaged they feel with their work overall. You could also conduct mini-surveys to ask employees if they feel engaged “in the moment.” Surveys are good because they prompt employees directly, but they can also suffer from subjective reporting bias, so they may not accurately reflect reality.
  • Retention rate. You can also indirectly gauge employee engagement by studying your own employee retention rate. Employees who are engaged tend to stick with their employer for a longer period of time, so a high retention rate is often reflective of high employee engagement. However, this isn’t universally true; there are some situations that may cause you to have a low retention rate, despite high employee engagement. You’ll need to study many variables to better understand this comprehensive picture.
  • Performance reviews. It’s also important to conduct periodic performance reviews, speaking to employees one-on-one about how they’ve performed over the past year (or past months, or whichever interval you choose). Here, you’ll be able to have a direct conversation with your employees about their productivity, their attitude, and their connection to the workplace. With both employee statements and supervisor observations, you can determine each employee’s relative level of engagement (and how to fix it). Unfortunately, these metrics won’t provide you with precise numerical data.
  • Exit interviews. Similarly, whenever you lose an employee, conduct an exit interview. Employees tend to be more honest and direct in exit interviews than they are in performance reviews or throughout their employment. It’s a good opportunity to learn which things to improve—even if it’s a bit too late for some employees.

Core Areas to Improve Employee Engagement

There are literally hundreds of things you can do to improve employee engagement, but all of them can be assigned to one or more of these core categories:

  • Workload distribution. Make sure each employee is doing tasks best suited to them, and that no employees are overwhelmed by a disproportionate workload.
  • Skills and education. Give your employees more chances to develop themselves. Employees presented with opportunities to learn new skills and educate themselves tend to feel more actively engaged.
  • Empathy and bonding. It should go without saying that practicing empathy and giving your employees more chances to bond can make them feel more engaged. This should manifest as both a top-down and peer-to-peer approach.
  • Culture and belonging. Your work culture plays a massive role in dictating how employees feel about each other (and about your workplace overall). You need to have a set of core values to connect your employees and provide them with a sense of belonging.
  • Recognition. It’s also important to keep employees engaged with some type of recognition. Reward your best employees, and publicly acknowledge their efforts.

The more you invest into employee engagement, the higher your productivity and retention will be. Experiment to see which tactics work best for your employees, and keep a close eye on your measurable results.

Source: https://www.smartdatacollective.com/how-can-you-measure-employee-engagement/

Big Data

AI may be the next Warren Buffett but there are challenges ahead

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From a disruptor to an integral part of our lives, artificial intelligence (AI) is the defining technology of our times, one that is rapidly changing how we work, consume and invest.

Its ability to sought, analyse and interpret huge amounts of data efficiently and quickly has seen it being deployed for trading and getting investment ideas. In most advanced markets, AI trading is gaining ground and is being used to develop trading strategies.

“Globally, asset management is increasingly being defined by artificial intelligence and machine learning (ML). Funds run by computers account for more than 60 percent of US trading activity,” said Kanika Agarrwal, CIO, Upside AI, which does machine-learning-based investing.

AI is unbiased, unemotional and has no specific style of investing. A good algorithm is dynamic and can test and refine trading strategies looking at market trends. It can do what analysts do—gather information, data and evaluate them to come up with suggestions.

“It can consistently find alpha, which is difficult for human managers who thrive in some market cycles but not in others,” said Agarrwal.

“Globally trading activity (short-term, high frequency, technicals, etc.) is largely run by technology now. Even passive ETFs have surpassed active managers in AUM in the US,” Agarrwal said.

She is of the view that the next step up for AI will be fundamental investing.

“We believe the next great investors like Warren Buffett and Charlie Munger are going to be AI. Benjamin Graham and Warren Buffett have been big believers in investing using systemised rules and staying away from emotions. The best way to follow rules unemotionally is the use of AI and technology,” Agarrwal said.

While developed markets seem to be rapidly getting acclimated to this technological revolution, emerging markets like India will take some time to see its dominance in investing.

“In India, while investing is largely people-driven, I believe we will see structural shifts in the next decade as our markets mature and alpha becomes more difficult to find. We will increasingly see more products like ours trying to find different approaches to investing in using AI,” Agarrwal said.

AI’s biggest strength is its absolute dependence on data and uses algorithms to understand the market and its cycles. This is the reason AI is being used in the investment and wealth management industry globally.

Mihir K Malani, Founder of FinTech startup, Nerve Solutions pointed out while the eventual aim is always to improve returns, the process usually involves multiple steps like picking the right stocks based on historical trends, deciding upon the investment size, identifying and predicting trends, etc.

“A commonly adopted approach is to use ML models to categorise clients based on their profiles, investment preferences and risk appetites and letting the model arrive at the most suited investment strategies for them,” Malani said.

One of the biggest advantages of a well-developed AI model for investment is its ability to avoid pitfalls and predict drawdowns successfully, he said.

“Also, a good way to measure the efficiency of a model is through the number of false positives generated by it. The lower the number, the better and more trustworthy the model,” Malani added.

The challenges

Even though AI appears to be an inevitable force in investing, there are challenges ahead.

While it is easy to access large sets of structured financial data to build machine-learning models, there are several challenges associated with developing a model that works.

Agarrwal of Upside AI believes that the challenges of AI are true across industries, including investing–data quality, the quality of the model built, lack of talent in India to build these machines, solving qualitative investing issues like corporate governance and wider acceptance of the technology.

Differentiating genuine patterns and coincidences is among the biggest hurdles one may face while applying AI to investing.

“At times, mere coincidences give an illusion of correlation. Inability to identify these could lead to extremely inaccurate models,” Malani said.

Identifying the right features and then designing the model is a challenge.

“This is a common challenge often faced while developing AI models for derivative instruments. With a number of factors involved in the pricing of a derivative contract, missing out on the right features could lead to seemingly correct but erroneous models,” Malani said.

Besides, embedding geopolitical factors within a model is also a challenge.

“While incorporating price and volume information within an AI model is fairly procedural, it is extremely difficult to account for factors that lie outside of the markets but have a profound impact on market movements. Such factors often are the reason for models to fail,” Malani said.

Despite these challenges, AI is the future of investing, one that opens up a lot of possibilities for investors and managers alike.

Source: https://www.fintechnews.org/ai-may-be-the-next-warren-buffett-but-there-are-challenges-ahead/

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InsurTech platform provider Novidea secures $15 million in Series B financing to support global growth

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InsurTech platform provider Novidea secures $15 million in Series B financing to support global growth

Novidea, a leading global provider of the data-driven, cloud-based platform that enables brokers, agents, and MGAs to drive operational efficiencies and growth across the entire distribution lifecycle, today announces the successful completion of $15 million in Series B financing. The round was led by JAL Ventures Fund II, with the participation of existing investors including KT Squared LLC and 2B Angels.

We are excited to partner with JAL Ventures, as a highly valued new investor, and appreciate the continued trust of our existing investors, who have demonstrated their confidence in our strategy and market-leading product,” said Roi Agababa, Novidea CEO.

“We are seeing growing demand for our smart data-driven platform, with its powerful analytical capabilities and actionable intelligence. This investment will enable Novidea to meet this demand and continue its exponential global growth, while expanding its operations in the US, UK, and international markets. It will also accelerate product innovation to further engage with large, enterprise insurance firms and grow our team with a key focus on our customers’ success.” 

Yair Elbaz, Partner of JAL Ventures Fund, said: “Novidea is capitalising on two unstoppable trends: cloud migration and the increasing use of data-driven insights. Covid-19 has accelerated the adoption of cloud-based services and, five years from now, all insurance distribution will use this technology. Novidea is truly leading the way.”

Many insurance businesses are encumbered by legacy systems that are limited, inflexible, and expensive to update. With Novidea, customers benefit from a cloud-based platform that makes it possible to work from any device, anywhere. This enables accelerated growth and profitability through enhanced sales and customer service, and improved operational efficiency.

Looking ahead, Novidea’s data-driven, cloud-based solution, which has already gained significant traction with more than 85 brokers, agents, and MGAs worldwide, including the US, UK, EMEA, and APAC, is set to continue to make a huge impact on the insurance sector.

Source: https://www.fintechnews.org/insurtech-platform-provider-novidea-secures-15-million-in-series-b-financing-to-support-global-growth/

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Band Protocol Partners with digital asset data company Brave New Coin to bring decentralized price reference data to DeFi

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Band Protocol Partners with digital asset data company Brave New Coin to bring decentralized price reference data to DeFi

Brave New Coin (https://bravenewcoin.com/), a leading data analytics and research company backed by Techemy Ltd, has joined forces with Sequoia-backed cross-chain data oracle platform Band Protocol to bring decentralized price reference data to the rapidly growing smart contract application ecosystem.

Band Protocol and Brave New Coin will work together to bring the globally weighted average spot prices for up to 1500+ digital assets through the BandChain decentralized oracle network. This will allow smart contract developers to readily integrate and utilize these spot price oracles on any blockchain platform. Band Protocol has already been integrated by leading smart contract platforms including Ethereum, Binance Smart Chain, Cosmos, Polkadot, ICON, Waves, and Matic Network.

“Brave New Coin is an early adopter and supporter of DeFi protocols, having launched the first crypto pricing data oracles for smart contracts in 2016,” said Fran Strajnar, CEO of Brave New Coin. “More recently, Brave New Coin has launched a tradable DeFi Index, of which the BAND token is a constituent. Together with Techemy Group, Brave New Coin and Band Protocol are leading the way in bringing scalable, decentralized and non-custodial products and solutions for trading, investment and analysis for smart contract developers to seamlessly utilize.”

“Working with established and reputable enterprises such as Brave New Coin will be pivotal to Band Protocol’s success as we collaborate to provide a commercial solution that protects intellectual property and data privacy while enabling the smart contract world to interact with external data sources,” said Soravis Srinawakoon, CEO and Co-Founder of Band Protocol.

This long-term partnership will also enable premium data source owners with paywalls such as Brave New Coin to automatically collect revenue on-chain starting next year. Band Protocol’s flexible oracle design benefits all stakeholders by allowing developers to create custom-made oracles with web APIs within minutes as well as enabling enterprises to commercialize their data by creating premium oracles for developers to integrate.

The Global Weighted Average Spot Price (GWA) provided by Brave New Coin works by providing a fair price for any tracked digital asset from near real-time trading across a global network of top crypto exchanges. With intraday, end of day price and volume inputs updated at a 30 second tick interval, developers in decentralized finance will be well equipped to build trustless applications using an independent, reliable, third-party price discovery oracle.

Source: https://www.fintechnews.org/band-protocol-partners-with-digital-asset-data-company-brave-new-coin-to-bring-decentralized-price-reference-data-to-defi/

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Sphero spinout Company Six launches throwable, video-streaming wheeled drone for first responders

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Sphero, the Colorado-based company best known for its programmable robots, in May announced the spinoff of Company Six. CO6 is focused on commercializing intelligence robots and AI-based apps for military, EMT, and fire personnel and others who work in challenging situations. Today the startup took the wraps off ReadySight, a one-pound, throwable robot built for “dangerous and difficult” jobs.

Robots make sense for first responder scenarios, as novel research and commercial products continue to demonstrate. Machines like those from RedZone can autonomously inspect sewage pipes for corrosion, deformation, and debris in order to prevent leaks that could pose health hazards. And drones like the newly unveiled DJI M300 RTK and Parrot Anafi Thermal have been tapped by companies like AT&T and government agencies for maintenance inspections and assistance in disaster zones. CO6 appears poised to carve out a niche in this market, which is estimated to be worth in excess of $3.7 billion.

According to CO6, ReadySight streams video over dedicated first responder and commercial LTE networks. Controlled by a smartphone, technologies integrated into the robot allow for “day and zero light usage,” as well as autonomous and semi-autonomous driving and patrolling modes, two-way audio communication, and unlimited range and usage over cellular. In addition to a speaker and microphone, a white light headset and infrared illuminator, a foldable “tail,” and a time-of-flight distance sensor, ReadySight sports a Sony camera sensor with a 120-degree wide-angle lens and lens shield and a motion sensor paired with a front indicator LED.

ReadySight can stream to viewers on the web, with streaming plans starting at $99 per month and first responder plans starting at $149 per month. Both subscriptions include unlimited streaming via priority networks and a free replacement robot if ReadySight is lost in the line of duty.

CO6 envisions ReadySight being deployed in the course of accident investigation, exploring tight or unknown spaces before someone enters, and acting as a sentry to keep eyes on critical areas like crime scenes. The company says ReadySight is expected to ship in Q3 2021.

CO6 began as Sphero’s Public Safety Division, the brainchild of former Sphero CEO Paul Berberian and Jim Booth, both of whom have backgrounds in military service. The products and services it hopes to deliver — which will include a cloud-based analytics and monitoring platform — will be designed to maintain safety and situational awareness and improve decision-making in the field for critical incidents and everyday operating environments.

To fund the productization and market entry of its initial products, CO6 raised a $3 million seed investment from Spider Capital and others, with participation from existing Sphero investors, including Foundry Group, Techstars, and GAN Ventures.

Source: https://venturebeat.com/2020/11/24/sphero-spinout-company-six-launches-throwable-video-streaming-wheeled-drone-for-first-responders/

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