Activating data on the move
KPMG helped a 5G infrastructure provider reinvent its business model to become a revenue-driving force in data analytics.
Client
A large metropolitan subway communications provider
Sector
Telecommunications
Project
Business model transformation
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Client challenge
As a leading 5G neutral host fiber infrastructure company and the provider of wireless connectivity for one of the largest public subway systems in the world, our client continuously captured a deep and ubiquitous well of data. Wanting to provide an additional level of service and present value-added offerings as they expanded into new markets, the company recognized a pivotal opportunity—to not only put their data to use and better serve their riders, but also create net new revenue streams derived from the data they were already collecting. The company’s partners expressed strong interest in this information, as they viewed it as an opportunity to access and utilize critical data insights to help accelerate their own ability to cut costs, improve operations, and provide a more enjoyable rider experience.
This forward-thinking company sought to maximize their data management capabilities, process the complexity of raw data they’d captured, and ultimately build out their capabilities to activate the data themselves. To become a data-first company, they would require strategy, data scientists, the ability to harvest and mine data at warp speed, and the right team of people to help pinpoint and connect the data dots.
This client chose KPMG for our data science acumen and assets, artificial intelligence capabilities, and analytical prowess.
Approach
To achieve the desired new data-centric business model, they sought external support to make their vision become reality. Based on our data science acumen and assets, artificial intelligence capabilities, and analytical prowess, the organization engaged KPMG for a 10-week period to analyze and activate their data. Rather than let the data decide what the company should do, we took a broader view. In order to best understand the value of our client’s data, KPMG took a parallel approach to the problem.
Our first team ingested and identified what data assets were available. A deep understanding of data type availability as well as their relative characteristics (completeness, freshness, collection frequency, etc.) was critical in understanding its value. We also augmented and enriched the company’s data with KPMG Signals Repository data.
Our second team assessed and prioritized market opportunities by interviewing our client’s customers, partners, and ecosystem, understanding their business needs and pain points to identify potential use cases. We built proofs of concept using machine learning algorithms to map rider origin, route, and destination. Segmenting rider movement characteristics to identify traveler habits helped us understand delays and rider platform congestion and differentiate among tourists, families, workers, shoppers, and event participants based on origins and destinations.
Based on this information, we were able to build a portfolio of transit solutions—called “smart transit”—that can be plugged into any global transit authority’s existing Wi-Fi data, avoiding additional infrastructure investment. Now, transit authorities can better understand in real-time their points of crowding and ridership, and route trains more efficiently and safely in response to improve the customer experience. They can identify marketing and advertising opportunities and support traveler information for major local events.
After developing proofs of concept, we analyzed the company’s capabilities and designed a target operating model to support an entirely new business. No longer a basic infrastructure provider, the company is in the process of becoming a force in data and analytics—activating and monetizing its data while creating new products for its transit authority customers to capture virtually unlimited opportunities.
In order to bring this vision to life, KPMG:
1
Worked with our client’s team to develop a detailed 18-month roadmap to guide product development as well as the organizational design to support the new products.
2
Phased go-to-market approach helped quickly capture low-hanging fruit while minimizing risk and helped apply lessons learned for future phases.
3
Not only leveraged our alliances, but also the systems, tools, and talent to execute it. Data dots connected. Business model transformed.
Benefits to client
KPMG helped our client transition from a legacy infrastructure player to an entirely new business model. Now, as an analytics service provider, they can focus on identifying additional revenue streams that matter to their current and potential transit authority customers. In the process of helping our client develop 25 use cases, KPMG demonstrated how to:
1
Continuously analyze market trends.
2
Gather current customer, partner, and competitive intelligence and predict consumer behavior.
3
Enhance business forecasting and decision making.
4
Determine strategies to best leverage their new assets to better serve their global customers.
Why KPMG?
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The right approach to leveraging data is to lead with market impact, not data
Begin with the end in mind. What impact are you looking to make? Then consider the action you need to take. What decisions have the potential to lead to those impacts? Then ask yourself, what insights do those decisions require? Then finally, what data is required to drive those insights? Data is the enabler, the tool, to reach the desired outcome.
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Closing gaps in data and capabilities can be the key to success
Once the data required to drive insights is defined, we ask if the client is already collecting that data? Clients are sometimes surprised by the data assets that can be utilized versus what they actually have. They may also believe their data processing capabilities exceed the reality. Closing those data collection and processing gaps can actually be the catalyst to success.
Meet our team
Sagi Abiri
Principal, Advisory, KPMG US
Sagi Abiri
Principal, Advisory, KPMG US