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MoveInSync Is Applying AI & ML To Make Corporate Commute 2X Faster


MoveInSync Is Applying AI & ML To Make Corporate Commute 2X Faster


When we talk about technology and innovation, India’s growth story has always been inspiring. Today, start-ups have evolved, and innovation is the hot button that is driving the nation’s business ecosystem. From a business perspective, concepts like e-cars, ridesharing, cab aggregation, hotel aggregation or any kind of shared economy is gaining significant focus with its growing user adoption. These domains have achieved maturity in the growth curve and thus provide the industry with a new set of opportunities and challenges. That is not all, even the stakeholders, customers and the employees in this ecosystem are also in the maturity cycle of the growth curve.



Founded in 2009, MoveInSync is one such startup that is thriving to become a crucial player in the ecosystem. And to know more about the industry and the growth story of the company, we talked to Akash Maheshwari, co-founder and CTO of MoveInSync.

Making Office Commute Better

The company started out as a carpooling service called RideInSync; however, it didn’t get the tractions as it was ahead of time and due to low smartphone penetration back then. Also, the employee transport sector was also highly disorganized; inadequate driver paper-work and safety concerns for women employees were making things difficult for both the company as well as the employees.    

In 2010, the company was re-launched as MoveInSync, an employee transport management solution. It was envisioned to automate the corporate transport process and address the demand for a safe and reliable shared commute.

“The company has evolved dramatically in over a decade since its inception. We have metamorphosed from mere technology partners to an end-to-end office commute solution,” said Maheshwari. “We have diversified our business model to include B2B and B2C. We also envision a C2C model to meet the changing needs of the market.”

Today, MoveInSync caters to a rich customer portfolio, providing solutions to more than 100 organisations like Google, Microsoft, Adobe, Oracle, Wipro and other Fortune 500 companies across 200 office locations in 22 cities in India and Sri Lanka. And now it is aiming to tap into the APAC market as well.

Talking about numbers, in 2018, the company covered 400 million km in 19 million trips; in May 2019, it recorded nearly 250,000 daily active users and 7 million employee rides, covering 50 million km in 40,000 MoveInSync-powered vehicles.

“We are the largest office commute platform in the country and our growth has been phenomenal,” said Maheshwari.

Utilising AI and ML The Right Way

Today, artificial intelligence is at the heart of the transportation industry. The industry is leveraging its superpowers for control functions, pattern recognition, rule-based decision systems, self-learning processes, etc.

MoveInSync is also one of those companies from the industry that is working on AI/ML solutions to make optimal transportation plans. It analyzes historical data patterns to predict demand, identify supply gaps, predict travel times, suggest employee clubbing and cab deployments. 

According to Maheshwari, essentially, AI/ML is used in 3 areas: Routing, Demand Forecasting, and Sentimental Analysis.

Routing

MoveInSync routing algorithm is a self-correcting engine that periodically leverages AI engines to identify errors in its output and review execution data from the trip. It collects a large volume of data from over 40,000 cabs running on the platform daily. Meaning, it geotags the entire trip, capturing employee boarding points, the route followed, and travel times between milestones across cities. And the AI engines periodically monitor this data to deliver higher employee satisfaction and cost optimization. In addition, it reviews the changes made by the routers manually on the MoveInSync-powered intuitive route editor, AI engine corrects itself to create outputs which adhere to router’s preferences.

Demand Prediction

MoveInSync is using ML models to predict a demand pattern from an area at specific hours during the day for customer organizations. And in order to achieve this, the company has used “Time series forecasting”.

Once the available cab supply is mapped, any possible cab shortage can be identified early, and cabs can be arranged on time. By coupling the internal demand behaviour with external factors like weather forecasts, local events, holiday calendars for the city (including long weekends) road-closures, public transport work schedules, etc. MoveInSync predicts the area wise demand, enabling transport managers to utilize cabs to their maximum and ensure operational efficiency.

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Analytics

Talking about the analytics aspect, they run on the Jasper engine.  For most of the customers, MoveInSync has achieved 10 to 30% cost savings through analytics backing informed decision-making.  Areas like no-shows of employees have seen a significant drop. Also, the company’s analytics help organizations renegotiate the contract with vendors.

Customer Centricity

“At MoveInSync, customer satisfaction is paramount to our fabric and forms the bedrock of our company. It has been our constant endeavour to enable companies to manage their employee transport operations, better, and optimized to mitigate financial, security risks and reduce transport costs,” said Maheshwari.  

The company makes sure that it analyzes how it interacts with the product, and then measure these metrics to conclude the area of the problem — tracking, scheduling or any other gaps that might be present. Furthermore, its 20-member support teams are available for its customers to respond to emails and over the phone linking us to exact qualitative feedback from its customers. In addition, it also conducts ‘focused groups’ with the end employees to gather their feedback and areas of improvement.

“We believe that a business is a partnership of the product offered and the service provided; if both are in sync, then the great results are guaranteed. It is all about making a conscious effort of getting in touch with the customers directly or indirectly,” Maheshwari added.

The Roadmap Ahead

Looking into the future, the company believes that roadmap ahead for MoveInSync will largely be shaped by Data Science. The company has built a complex workflow and now it reckons that it should simplify this with technology and automation.

“We believe that there is potential to expand the benefits of employee transportation to newer markets and build a global footprint. And the road ahead also outlines our growth in the B2C space where we will need to focus on the user experience to ensure user satisfaction,” Maheshwari concluded.



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