Artificial intelligence

How can AI help you with Location Optimization


Does your company from time to time need to find the optimal geographical location for something? Perhaps you need to find the best spot for a new store, storage facility, windmill or food truck? To solve this we can use either of two different methods. But first we need to collect a number of location examples. The more examples we have the better the AI will be able to understand what we want it to learn. For each location we need to add as much data as we can find, like:

  • Average outside foot traffic
  • Proximity to highway
  • Windy days per year
  • Number of people working in the area
  • Day of week

If we treat this as a “classification” problem we also need to label every location as “good” or “bad”. We then train the AI on this data. Now we can show the AI new locations and it will tell us (classify) if it considers a particular location to be “good” or “bad”. Pretty neat.

Sometimes the good vs bad classification is not fine grained enough. Then we can treat this as a “regression” problem instead (meaning the AI will predict a number for us). To do this we need to assign a number instead of a label to each location. So a top location could be a 10, a bad location 1, and others somewhere in the middle. We train the AI and it will now be able to give us a number for new locations we show it. This way we are able to rank a list of possible new locations. Even neater!

Why do this

If you need to choose between several possible locations, why would you not want to pick the best one? Of course you want the one you hope will be attracting the most foot traffic, take the least time to drive a truck to, or generate the most electricity. As in many use cases us humans normally have a hunch, but there are too many interacting variables to know for sure. This is where the AI can shine and help us out with its opinion about something based on the examples we have trained it on. So this is a perfect way to make sure your company maximizes its revenue!

How do I get started

You probably have a list of potential locations you are choosing from as well as the example data you want to base your decision on. You need to enrich each item on this combined list with the data you want the AI to consider. This could mean that you have to dig into external data sources, maybe you have to buy statistical data or weather reports, or even just perform lots of web searches. You can even add images of the neighbourhood as input data about a location! Remember, the more relevant data you have, the better the AI’s predictions.

For a retail store chain, here are some example data points to collect:

  • Distance to nearest city center
  • Distance to nearest highway
  • Number of people living within 5 km from location
  • Store size
  • List of all departments in the store

Now when you train an AI with this data perhaps it will find the relationship that “big store, close to highway and has many departments” will be rated as 8. But perhaps it will also find that “small store, close to city center with many people living nearby” is a 10.

For a food truck here are some example data points to collect:

  • Street
  • People working in the area
  • People living in the area
  • Day of week
  • Day of month
  • Season
  • Today’s special was X

This might reveal that “on tuesdays in the summer” going to Street A will always be your best choice.

Remember that you yourself have rated the examples, so the AI will put a higher valuation on the things you have shown it to be more valuable. Hopefully this gives you a better material on which to base your final decision.

If you want to learn more about AI please visit: praktisk.ai

Webinar

Cloud optimization webinar

Join our cloud optimization webinar the 25:th of August between 08:30 to 09:15. Learn how to lower your monthly AWS bill with 40-50% by optimizing your AWS accounts.

Managing cloud infrastructure is different to managing infrastructure on-prem. It’s easy to provision new resources but it’s equally easy to forget to decommission resources when they’re not needed. Further more, performance tuning is often not part of daily routines and only performed when there are performance problems. Optimization is not supposed to be performed occasionally but rather on a regular basis to ensure a cost effective use of cloud computing.

Join this webinar to find out how you can work with continuous optimization to lower your monthly AWS bill. You can also read this blog post which includes a financial comparison between optimized vs. non optimized AWS infrastructure.

Join our webinar the 25th of August at 08:30 to 09:15.

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COVID-19

4 ways to reduce cost and increase liquidity. #4

Many companies are under tremendous financial pressure due to the COVID-19 virus. We sat down to figure out what we can do to help and came up with 4 ways of how we can reduce cost and increase liquidity in the short term for a company. We are posting these 4 ideas in a blog series and in this blog post, we will present the fourth and final idea in the series to improve your financials – optimize your AWS infrastructure.

#4 – Optimize your AWS infrastructure

This fourth and last post in our series of “4 ways to reduce cost and increase liquidity” we will focus on optimizing your AWS infrastructure. There are great potential to reduce your AWS bill by optimizing.

Managing cloud infrastructure is different to managing infrastructure on-prem. It’s easy to provision new resources but it’s equally easy to forget to decommission resources when they’re not needed. Further more, performance tuning is often not part of daily routines and only performed when there are performance problems. Optimization is not supposed to be performed occasionally but rather on a regular basis to ensure a cost effective use of cloud computing. You can read more about cloud cost optimization.

We have performed a number of optimization projects during the years and we always identify substantial and remarkable savings. If you need to find quick ways of reducing your costs, optimizing will be one tool to use to bring good news to your CFO.

Example – a company with a monthly billing of 150 000kr

You need to consider this example as generic because it very much depends on what services you use, what share of serverless vs. EC2 instances you have etc. For the purpose of this example, we assume you have a quite common setup in AWS which we normally find when we engage with customers.

This company have a monthly billing of 150kSEK per month. We’re comparing the annual AWS cost as-is with an optimized service from us.

Year 0 represents the investment year and in this case it includes an initial analysis of 30kSEK. After reviewing the infrastructure, we are able to present a more detailed business case with a much higher precision than this example.

This company have an annual cost of 1.8MSEK per year. They would need to invest 30kSEK to enable the optimization service from us which in turn will lower the AWS cost to 1MSEK per month including a continuous optimization service from us. The total cost as-is would be 10.8MSEK over 6 years compared to 6.3MSEK for the optimization service.

AWS infrastructure as-is versus an AWS optimization service

The graph below shows yearly savings and accumulated savings over 6 years. This company would save 700kSEK the first year and 756kSEK the following years. The return on investment in this example is 7.2 months. The accumulated savings is 4.5MSEK over 6 years, or 42%.

Accumulated savings of an optimized AWS infrastructure

As mentioned before, there are of course a lot of ifs and buts in any calculation and specifically in this case as it heavily depends on how the infrastructure is set up and managed today. We have created a template for helping companies calculate a comparison between as-is and an optimization service from us. The initial analysis will reveal the potential in your specific company.

Please contact me or any of my colleagues if you would like to do the exercise for your company, we’re here to help.

This is the final example of how we can help you reduce costs and increase liquidity in the short term. Please check out the previous 3 ideas.

#1 – Hardware refresh

#2 – [ insert integration product here ] replace

#3 – Incident automation

You can also watch a webinar about optimization.

AWS optimization webinar in Swedish

AWS optimization webinar in English