This article is an excerpt from the first report: The Democratization of Analytics for Transportation and Logistics.
A copy of the full report can be downloaded here.
In Part 1A of this series, we explored how the data being produced by transportation and logistics systems can be used to create a data-driven enterprise, as well as the obstacles to achieving an analytic advantage. Here in Part 1B, we look at how solution provider capabilities can be leveraged to overcome some of these obstacles.
Leveraging Solution Providers’ Expertise and Pre-integrated Datasets
Data wrangling is best done by those who know the data the best — those who work with the data and systems every day. One option is to see whether the software company that provides your transportation and logistics solution has the required data science expertise, has already done the data-wrangling for a wide array of common use cases, and has the tools and services to rapidly incorporate your unique data. This can save a tremendous amount of time and money, allowing an organization to get started with advanced analytics capabilities almost right away. Some things to look for when assessing whether or not a logistics software solution provider has the right capabilities to provide the analytic capabilities you need include a dedicated team of data scientists, robust analytic technology, customer-specific data integration services, data wrangling capabilities, and a comprehensive suite of transportation and logistics solution functionality. Below are some questions to ask and things to look for when assessing a solution provider’s analytics services and capabilities.
Dedicated Data Science Team
How many data scientists does the solution provider have who are dedicated to providing these services and what is their experience? As this is the scarcest resource, it can be an important differentiator to achieving results.
Robust Analytic Technology
The analytics technology from a solution provider may be a mix of software they developed in-house and ISV-developed tools.1 Some things to look for include:
- Visualization capabilities that are versatile, intuitive, and easy to use
- Customizable live data dashboards
- Ad hoc analysis and reporting
- Database connectivity preconnected to a wide variety of databases, especially the ones your organization uses and cares about
- Support for NoSQL, unstructured, and streaming data (e.g. IoT data feeds)
- Scalability for ingesting and managing large volumes of data (depending on your needs)
- Ease-of-use for business users (business analysts, power users, and casual users)
- Granular security and personalization
- Data quality tools for finding and correcting deficiencies in data with minimum manual effort
- Responsive UI and use cases to include mobile analytics and mobile data collection
- Embedding of analytics into applications and workflows — prebuilt into the solution providers’ applications, but also the ability to embed analytics into your own and third-party applications
- Active user and developer communities can make a big difference in finding answers and support
Customer-specific Data Integration Services
We recommend looking for a solution provider that offers tools and services to integrate your own company-specific data, such as your enterprise transactional data, including orders, shipments, BOLs, customs filings, etc., as well as master data (customers, suppliers, carriers), planning data, and any other data you possess that might be useful for analytics. This may include data in spreadsheets and other individual documents.
The provider’s integration services should also incorporate unique external data you may use or need such as weather, traffic, and data that may be specific to your industry or company’s needs (like specific commodity prices or event schedules). This should be more than a set of APIs the solution provider hands to you and says, ‘have at it.’ Unless your IT shop is set up for and wants the additional workload of building and maintaining those integrations, you may prefer a provider that can do the integration work and maintain the integrations over time. Ask about their integration methodology, services, tools, and ongoing support to better understand what they really provide.
Data Wrangling Capabilities
When evaluating a transportation and logistics solution provider’s support for analytics, it is good to find out what level of data wrangling they have already done and are willing to do. Some specific questions to consider:
- What is their overall approach, methodology, tools, and resources for data wrangling?
- What use cases have they already implemented? What data and systems — both from the solution provider and from the customer — are involved in those use cases?
- What kinds of tools and methodologies do they have for cleaning up and organizing the data?
- What is their security architecture and approach for data in the analytics data set?
- What varieties of data do they handle?
- What steps do they take to ensure performance and scalability, such as denormalization?
- What steps, if any, do they take to adjust for bias in the data?
Comprehensive Suite of Transportation and Logistics Solution Functionality
It is better to try to find a solution provider that can fulfill all of your transportation and logistics needs and that has already done the data 
wrangling and provides the kinds of analytic capabilities and integration services described above. For example, a solution suite that can manage parcel, TL, and LTL; can manage both private fleet and purchased transportation ; across all modes ; has global trade management capabilities ; supports pooled distribution ; offers telematics hardware and software ; dock scheduling and yard management ; and eCommerce integration. Going with a single analytics-capable provider that can handle all of your transportation and logistics needs will simplify your analytics strategy and implementation, compared to trying to stitch together offerings from multiple providers.
Finding the Right Solution Partner Makes a Difference
Partnering with the right solution provider that has the right combination of transportation and logistics software capabilities, analytics tools and expertise, and data wrangling services can help jump-start analytics efforts, dramatically reducing risk, upfront investment, and time-to-value to achieve an analytics advantage.
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| Figure 1 – The Right Solution Provider Partner Can Overcome Barriers to Achieving an Analytics Advantage |
Unlocking the Analytics Advantage
The process of digitizing a company’s supply chain and logistics processes and systems is a journey. Even early steps on that journey start to generate valuable data that can be mined. In fact, many companies are sitting on a goldmine of largely untapped transportation and logistics data. Part of the reason the value remains locked up is the scarcity of data science talent and the time and resources to wrangle data. These challenges can be overcome by choosing a full-suite transportation solution provider that has invested the time and resources to acquire the necessary data science talent and has done the heavy lifting involved in wrangling data across their suite, as well as their customer’s systems.
Applying analytics can be like a near-sighted person putting on a pair of glasses for the first time. All of a sudden everything that was blurry comes into focus. As the use of analytics matures in a company, it can become an ‘insights engine’ for them, highlighting not just where problems are, but the ‘why,’ what is causing those problems, what are the potential solutions, and the tradeoffs between those potential solutions. As a company becomes more adept at leveraging these insights, a true ‘analytics advantage’ is realized.
Part Two of this series looks at how analytics uses real-time location data, combined with orders, plans, proof-of-delivery, vehicle data, and more to drive significant improvements to fleet and driver performance.
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1 ISV = Independent Software Vendor. One source for evaluating these kinds of tools is the Gartner Magic Quadrant for Analytics and Business Intelligence Platforms. The top four ISVs in Gartner’s 2019 evaluation were, in this order: 1) Microsoft Power BI, 2) Tableau, 3) Qlik, 4) ThoughtSpot. It is notable that Microsoft is rated quite a bit ahead of all the others and has been ranked #1 in Gartner’s evaluations for the past 12 years in a row. — Return to article text above
To view other articles from this issue of the brief, click here.