Vertical ML/AI Startup Creation Weekend

Sector analysis

Vertical description

Construction is the work of making or building something. It starts with planning, design, and financing; it continues until the project is built and ready for use. Large-scale construction requires collaboration across multiple disciplines. A project manager normally manages the job, and a construction manager, design engineer, construction engineer or architect supervises it. Those involved with the design and execution must consider zoning requirements, environmental impact of the job, scheduling, budgeting, construction-site safety, availability and transportation of building materials, logistics, inconvenience to the public caused by construction delays and bidding. The construction sector is a broad sector composed of many segments such as infrastructure, commercial, and residential construction. Residential seems to be the most interesting but ideas could come anywhere from furniture to floating bridges.

How big an opportunity space is this, how is it growing, and what’s driving that growth?  

The US construction market is estimated to be $1.32 trillion. The global market is $17 trillion. Growing at 7.6% annually driven by residential market trends and the economy.

What are the segments/pockets?

There are many ways to segment the focus area. The fastest growing construction segments are single family, office, education, public buildings and roads/bridges. You can also look at it in terms of materials used. Lumber, Gypsum, Cement, and Aggregates markets are growing the fastest. Self Healing products are experience extremely high growth as well. The economy’s strength is a major driving trend of construction.

What is the technology spend and trend in this category, or the revenue growth rate of companies in the category (whichever is applicable)?

Gartner ranks Construction as dead last in IT investment compared to other industries. Construction revenues are expected to grow at 4.5% dependent on population, government spending, and economic health.

What are the proof points that success may be rewarded?

The top 10 construction companies all have over $5 billion a year in revenue. Total market revenue is very dispersed providing an opportunity. (72k companies in CA)

• Recent M&A:
  

  • ModSpace by William Scotsman ($1.2B) - innovative modular construction
    

  • Viewpoint by Trimble ($1.2B) - Project management software
    

• Rising stars:
  

  • Katerra-($1.2B raised) - Optimizing construction processes
    

  • PlanGrid($69M raised) - Cloud collaborative blueprints
    

  • Helix ($44M raised) - Custom GC software to create advanced building
    

  • Honest Buildings ($47.8M) - Automate bids and procurement
    

• Early seeds:
  

  • Plant Prefab ($10M raised) - Prefabricated sustainable homes
    

  • Raken ($12M) - Daily construction work flow tracking
    

  • Drone Base ($19M) - Imaging from the sky for building and real estate
    

At a high level, what problems are there to be solved using technology?  

• Time it takes to get construction quote?
  

• Where do consumers start a project?
  

• Can I DIY projects previously too difficult?
  

• Improvement of construction processes utilizing tech.
  

• Automation opportunities?
  

• Utilize the gig economy for construction?
  

• Actually stick to budget and timeline?
  

• Can we build homes cheaper?
  

• Is there natural disaster proof construction?
  

What current trends are driving change in this category?  

• Green technology
  

• Modular and prefabrication
  

• Employee safety
  

• Difficult to find laborers
  

• Better sourced materials and increased costs
  

• 820k new houses built every year. $84 billion spend on US commercial construction in 2017.  >$250 billion spent on roads, schools, and public infrastructure.
  

• Self-healing technology
  

• Wearables
  

• Drones/Robotics
  

How specifically can ML/AI change the game in this category?  

• Optimize project management
  

• Improve worker performance by identifying strengths/weaknesses
  

• Automate paper processes
  

• Integrating different systems
  

• Specialized labor tasks based on performance
  

• Improve risk management and job site safety
  

Investment hypothesis / rationale

The market is massive and full of universal problems. Because of the lack of technology in construction there are likely opportunities to digitize and improve process by utilizing ML/AI.

What adverse conditions / headwinds are there for a play in this space? What makes it difficult?

• Lack of expertise
  

• Certified way of building
  

• Government involvement
  

• Barriers to entry
  

Data sets

Your novel business idea should be grounded in real-world data with plausible machine-learning/analytics on top. We've compiled a collection of datasets from which to gain inspiration. Note that you are not restricted to basing your idea on the data sets below. You may discover other open source data sets that inspire your creativity or you may bring your own proprietary data sets if you wish.

Many of the datasets below are from Kaggle, Figure-Eight (Crowdflower), Data.World, etc. The advantage of these datasets is that many have been cleaned and normalized and are ready to be explored with ML and data science tools. Note that the use of these datasets is often intended for research purposes only. Be sure to read any associated license agreements to understand if there are commercial restrictions if you plan to continuing using the data after the workshop is over.

Resources

• https://www.mckinsey.com/industries/capital-projects-and-infrastructure/our-insights/the-new-age-of-engineering-and-construction-technology
  

• https://www2.deloitte.com/content/dam/Deloitte/us/Documents/Real%20Estate/us-engineering-construction-technology-infusion.pdf
  

• https://assets.kpmg.com/content/dam/kpmg/cn/pdf/en/2017/09/global-construction-survey-2016.pdf?_ga=2.240398407.577987305.1539699402-942976568.1539699402