Further, Faster, Cheaper: How Data Analytics Helps Mobility Businesses Go an Extra Mile
A practical guide for mobility businesses on how to make the most out of their data and build data-centric solutions. … Read More
The past two years’ events have re-wired business stakeholders across industries to become data-driven. In 2022, nobody questions the value of data in nurturing business growth and speed. Instead, companies are striving to secure the best data science resources that will allow them to establish a consistent, repeatable framework for data-driven decisions. Data science outsourcing might be just what they need to accomplish that goal.
Let’s not talk about how data science helps businesses thrive. By this time, savvy stakeholders will already know that data is the lifeblood of their prosperity and efficiency. Data tools like interactive dashboards and reporting have become a staple in modern enterprises (78 percent of them use dashboards or interactive analytical apps, according to MicroStrategy’s 2022 report). Moreover, 60 percent of enterprises use data analytics to drive process and cost efficiency, according to the 2020 edition of the report.
An upgrade from that—deploying software that collects, aggregates, and processes data to offer insights—is proactively participating in the data revolution by defining use cases that custom data science solutions can serve, solve, and augment. And that revolution is already happening in enterprises globally. Think about data science teams building AI-powered interfaces that support onboarding customer journeys across the web and mobile apps. Or logistics data departments using data analytics to prevent various risk scenarios (tariff hikes, port strikes, inclement weather) from impacting deliveries.
The data-driven trend is so widespread that Gartner predicts that by 2024, three-quarters of enterprise decision-makers will have established a data and analytics center of excellence to insulate their companies from disruption and strengthen competitiveness. But you don’t need to be an industry behemoth (regardless of vertical) to embed data in every process, team, and decision. The data-driven culture is for organizations of all sizes to embrace. So if your company cannot invest in building expert capabilities internally, data science outsourcing is the answer.
If we were to describe an ideal data science expert in one word, it would be a multidisciplinarian. According to the scientists quoted in Harvard Business Review, data analysis takes only about 20% of a data scientist’s time. The rest is spent on preliminary work, such as research, verification, analysis, and coding—tasks involving various skills.
The multifaceted nature of the data scientist profession is one of the reasons why the demand for that role exceeds the supply. And that trend will continue, as it is expected to grow by 268% within the next ten years. So, let’s see what it takes to be a qualified data scientist:
Let’s pretend for a moment that the skills shortage in the data science job market does not exist. Even then, the costs remain a burning issue when building in-house data science teams. In the US, the estimated total pay for a data scientist is $120,508 per year. Varied reports reveal that data scientists in Germany earn between €55,700 and €63,000 per year. In the UK, their salaries start at €60,000. And this is just a fraction of the total cost of sustaining a single position in-house for a company.
Apart from the lack of available skills and high pay expectations, another argument against hiring in-house data scientists is the dynamic nature of data-driven projects. Demands are constantly shifting. For example, now, you may want to build a powerful data engine that links fuel use with mobility patterns of individual drivers or optimizes routes to preserve the residual value of your fleets. But once that’s done, your company may not have the data needs sufficient to sustain a team of highly-paid specialists full time.
For these reasons and more (which we are happy to discuss with you on a quick consultation call), data science outsourcing is a popular option among future-driven companies that want to protect their growth. In this arrangement, an organization delegates all tasks related to data science to an external, specialized company that works exclusively on data science projects. These tasks include:
Hiring specialized support to fulfill one’s data science needs means you retain your intellectual property rights and ownership over the data and the insights, but hand off all work requiring technical data science expertise to an external team.
Today, companies are moving towards a truly data-driven mentality, where they don’t react to data insights but define business goals and use data as the means to achieve them. This approach, where data is treated as a continuously evolving product that matches the current demands of an organization, requires dedicated specialists who keep abreast of the latest technologies and can apply them hands-on in an agile manner. Outsourcing provides a golden opportunity for companies that can’t afford to hire an in-house data team to source such specialists. And there are numerous benefits of this solution:
Despite the numerous benefits of outsourced data science teams, partnering with an external vendor always carries some risks, especially as huge volumes of sensitive data worth thousands of dollars are concerned. To mitigate them, it is essential to discuss the following key topics when engaging with a data science services provider:
According to the report created by Mordor Intelligence, the value of the data science outsourcing market was nearing $3.04 billion two years ago. Experts expect this number to increase more than three times by 2027 (to around $9.45 billion). The dynamic growth of the data science industry, in combination with the significant skills gap, means that the demand for data scientists will continue to increase. Seeking a partnership with accomplished, trusted experts will allow forward-looking organizations to access data science capabilities essential to identifying future values, building customer-oriented products, and providing excellent services to enhance profitability.
A practical guide for mobility businesses on how to make the most out of their data and build data-centric solutions. … Read More
Remember the early days of the pandemic? Cities became ghost towns, and public spaces were no longer public, as everyone locked in to avoid getting infected. COVID has affected most aspects of our lives, and mobility was no different. With work and school going remote and traveling severely limited or outright prohibited, roads emptied. As a result, traffic remained light—even though driving was the only way to get a little taste of the outside world for many. … Read More
The invention of the gas-powered car by Carl Benz in 1885 wasn’t just another step in the history of mobility—this time, humanity has made a real leap forward. By making transportation more efficient and accessible, internal combustion engine (ICE) vehicles have affected all industries in one way or another. Over time, we started to rely on them so heavily that we now design our routines, lifestyles, and even entire cities around them.
But no king rules forever. Fast-forward to today, and after almost 130 years, the reign of combustion engine cars is slowly but surely coming to an end. A new contender is on the rise—electric vehicles (EVs). … Read More
According to various sources, a new car loses 9–11% of its value the moment you drive off the dealer’s lot. Over 2-3 years, its price may diminish by more than a half! Although it might seem that the situation is helpless, data science can provide a cure. Learn how applying the right algorithms on telematics data can help you protect and boost the value of your vehicles.
… Read More
A practical guide for car insurers to build customer-engaging products, expand services, and boost profitability in the post-pandemic times.
… Read More
Picture this. You’re driving back home after a long day of hard work. Exhausted from a series of back-to-back calls, starving despite that quick, half-eaten sandwich you rushed through between one virtual meeting and another. Dying to finally get well-deserved rest.
But just then, a sharp squeal comes from under the hood. Is it an issue with brakes or a loose or worn fan belt? Maybe the steering system went down?
Either way, your dreams of a good evening’s rest are now ruined, and you’re up for towing or an unplanned inspection. Both of which are going to cost you dearly.
Now, what if all of that time and hassle could have been avoided?
… Read More
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