Setting Your Budget for a BI project

Whether you know you’re going to need BI or you’re just trying to determine if it’s worth the cost you need to know what the costs really are. We’ve worked with customers in Calgary, Edmonton, Saskatchewan and British Columbia to come up with a budget for their Business Intelligence projects and find ways to minimize that expenditure. Here are some factors to look at when setting your budget for your analytics project.

  1. Sources of Data
  2. Initial project size
  3. Number of recipients
  4. Internal versus External Resources
  5. Type of Software and Brand
  6. On-Premise or SAAS
  7. Data Volumes
  8. Timeline
  9. Real time Versus Near Real Time Versus Batch
  10. Cost Overruns

Sources of Data

Sources of Data – since the whole purpose of business intelligence is to analyze data this is a good starting point. Do you know where your data is stored? Who has access to it? Is it in an easily readable format? What are the volumes of data? Are you looking to compare to external data like weather trends or social media? Knowing where your data is and how many sources is key to getting a feel for how long it will take to pull things together and provide access to the data. Multiple sources can make for a bigger budget – but also a greater value provided to end users who can then get a complete picture of the organization and impacts.

Initial Project Size

We always recommend starting small and building up to bigger projects. This reduces the risk to a limited amount and if things to go wrong the team can quickly learn from the issues and be on track for bigger projects in the future. Projects that can be delivered in 30, 60 or 90 days are ideal for starting out. Once the team has successfully delivered these short term projects then it may be time to move onto larger deliveries. Proving out the return on investment is key regardless of size but starting out with a short term delivery is helpful in many ways. Budgeting for a 30 day project is also much easier than determining the budget for a long multi-year project.

Number of Recipients

Paraphrasing an idea from “Think and Grow Rich” is the idea that the most success can be found by helping the most people. However, a bigger audience will increase the costs of your project both with software costs increasing and in the time and effort to gain consensus on each issue. The benefits of helping more people within your organization do have to be weighed out with the increases in costs. You can provide BI to a greater audience – but we recommend baby steps to get there to help keep costs to a minimum and to gain momentum.

Internal versus External Resources

A separate post needs to be written to cover all of the pros and cons of internal and external resources for BI projects. A general approach is to get external resources to help get you off the ground quickly and get the initial projects delivered, while training internal resources. This approach helps to set best practices and reduces costs over the long run. Once that project is delivered then maintenance and upgrades need to be considered.

Some companies are too small for a full service IT team for maintenance and ongoing projects – in this case it is helpful to outsource this type of role. When a task like adding a user is only done once every six months or so it’s easy to forget the steps and sometimes easier to call on external resources to complete these small support tasks rather than have a Full Time Employee assigned to do ongoing support when it comes up occasionally. Again, many considerations for resourcing but helpful to take a long term perspective even when looking at small projects as the costs can add up in a variety of ways.

If you have an experienced internal team it can be a great way to reduce costs over bringing in expertise – if not then a balance of internal and external can help keep costs down while delivering an advanced system on time and on budget.


It’s no secret that some software is more expensive than others. When looking at which one to go with you can look at the Gartner Magic Box for a good idea of the strengths and weaknesses of each product. There are many considerations for evaluating the software for a new project – do you already have software installed? Are you an Oracle/IBM/Microsoft etc. shop? Who will be maintaining it? How easy is it to get resources to work with this software? Is the software sold on a concurrent user basis or named users, PVU (size of your server) or other?

Software licensing is often different depending on the type of software – it’s good to ask how it’s sold and if there are better options for you depending on the number and type of users you are expecting. There are also Express versions of most software for small deployments or proof of concepts – or Software as a Service that reduces the upfront cost and is often better for companies who don’t want to handle software upgrades but just want to jump right into data analysis.

When looking at software costs it is important to remember there are often renewal costs to deal with. (Conditional on whether the software is on-premise or SAAS). Often renewal costs fall in the range of 20% of the initial purchase and increasing each year. Just one more item to consider when planning your BI project budget.

On Premise or Software as a Service (SAAS)

As mentioned above Software as a Service is an option for BI projects. This is a big consideration for project costs – do you want an on-premise solution or SAAS? There are many different considerations here; upfront costs, ongoing maintenance, data security and policies about the location of company data. As well this could impact whether the cost becomes an operational expense or a capital expense.

SAAS can significantly reduce the upfront cost of a project and in turn reduce the risk of the project, however there are other considerations like how the expense affects the financial books.

Data Volumes

Big data is completely relative to the systems that are handling the data and quite simply bigger volumes mean more work in pulling the information together and in hardware storage costs – even though these costs have been continually coming down in price.  Do you have hundreds of SKU’s or millions? Tens of customers or thousands? Sensor data that’s coming in by the millisecond or once a day or once a month? Frequent updates tend to create larger data volumes and more work in managing those data volumes. In turn this has an impact on your budget. Having an idea of your data volumes at the outstart of your investigation will help you decide on software and the impact on your budget.


Budget and timeframes go hand-in-hand and often can be balanced against one another. If you need this information yesterday the costs will be high in getting things together quickly and pulling a team together to complete all the work upfront. Often this is a matter of spreading out the costs or facing them upfront. However, if faster means you have to rely more on external resources and high-value expertise this could add additional costs to your project, particularly in comparison to slowly building an internal team to complete the tasks at hand.

Real time Versus Near Real Time Versus Batch

Real time data or the ability to see how things are changing as it happens is critical for alerts for equipment, servers, etc. and allowing for early warning of changes in your business. At the same time, it’s not always helpful to have real time data; when a report is constantly changing it means that every conversation is dependent on who looked at the latest report. This can result in individuals doubting the reports or having unnecessary conversations about the results simply because they changed since they were last looked at. Month over month and year over year reporting rarely needs real time data. Knowing how old your data can be is critical in deciding the type of hardware and software needed for the project. This is a key item to understand when planning your BI budget.

Cost Overruns

Understanding all of the above considerations will help mitigate cost overruns. Despite this, when starting the journey of understanding your business data things do come up. This may be as simple as extra discussions surrounding business rules that were believed to be well understood but the data shows otherwise, or unforeseen issues like network problems when moving large volumes of data. Other considerations include backup frequency and network/hardware infrastructure.

It often takes many months to get a full BI project started with a budget established and approved, a timeframe set, and an expected return on investment. Despite the length of time it takes these projects, it can be very important for companies to jump into business intelligence and key to gaining a competitive advantage in many industries. As well understanding these budget impacts will help to mitigate the risks to the project in general and the budget specifically.

Ask us for more information and how we can help you to make the most out of your BI project. Send us an email at or call at (587) 885-1090

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