As artificial intelligence and automation mature, exciting new business intelligence tools are proving their worth.
It’s hard to deny the results early adopters have seen from those technologies.
For companies struggling to balance business intelligence with other digital transformation efforts, however, the expense of building BI software seems prohibitive.
They need an option that lets them “punch above their weight class” without destroying the IT budget.
The Trouble With Modern Business Intelligence
Using traditional methods, the cost of incorporating AI and automation into business intelligence presents an enormous barrier to entry.
Both require specialized software and dedicated storage space. Companies interested in modernizing their BI practices had to build their own system.
This involved a massive up-front investment in both time and money.
How massive? Even with the actual algorithms and analytical software licensed from a third-party vendor, companies had to:
- Build on-site servers to store their data.
- Commission or buy analytics and management software.
- Hire a data science team to manage business intelligence.
- Physically maintain and protect the servers.
The process takes a long time to show ROI, and once it does things get complicated.
To continue producing results it needs a steady influx of data.
That means bigger servers, more data scientists to interpret results, and rising peripheral costs (physical security, server maintenance, higher power requirements).
The expense made modern BI methods inaccessible for all but the largest global organizations.
Without those methods, though, businesses have trouble staying in the game.
As CIOs realized the potential risks, demand rose for economical BI solutions.
Three game-changing strategies are helping companies regain their competitive edge.
The advent of cloud storage has done away with the need to build on-site servers.
Cloud databases function like renting a storage unit: monthly payments cover the actual storage space plus maintenance and physical security.
Because there’s less up-front investment, projects using cloud storage realize ROI in a shorter time frame.
Cloud storage has more than financial benefits. It’s fast and simple to set up. Scaling is as easy as upgrading a subscription.
The servers don’t need to be moved if the company’s physical location changes.
All things considered, cloud storage is hands-down the best option for responsive development.
Software As A Service (SaaS)
Building custom BI software is not always practical for companies without a clear vision of their BI needs.
For budget-conscious companies just exploring the high-tech BI space or for those with relatively routine needs, Software-as-a-service (SaaS) is a better solution.
SaaS can be loosely compared to cloud storage in that it’s a subscription service, but SaaS goes several steps further.
Instead of being simple storage, SaaS is BI software owned and maintained by a third-party vendor.
It’s accessed through the vendor’s site rather than being integrated into a company’s own systems.
SaaS software is usually designed for non-data engineers. That makes it intuitive to learn and use.
The pay-as-you-go subscription model is easy to budget for and has low start-up costs.
Some freemium options have no start-up costs, letting companies get a feel for how they’d use software before committing to premium features.
There are some drawbacks. Because SaaS software is designed for general use by non-technicians, its features may be limited or simplistic.
It’s hard to get exactly what is wanted in one product. Most companies end up using several different products to get the answers they need.
Data usually has to leave the company’s servers to be analyzed on the vendor cloud. That introduces a point of vulnerability for data breaches.
As security becomes a bigger priority, however, SaaS providers are creating solutions that better protect sensitive data.
Discussing security concerns with the vendor should alleviate most of this risk.
Consolidating Data and Analytics
One hidden cost of BI is labor. Especially when the budget is tight, employees are asked to do a lot of the data gathering and preparation manually.
This seems like a low cost solution - but it’s actually a very expensive way to do business intelligence.
When employees are asked to do their own data prep they lose as much as 80% of their workday to tedious, low-value tasks.
Their resulting data is pricier and less reliable than data prepared by software (which isn’t susceptible to human error).
Even when staff is given management tools, time is wasted correlating data from one system to another.
SaaS is easy on the budget, but it does mean using several “almost right” solutions rather than one custom system. 71% of companies admit to using 6 or more data sources while doing BI.
Commissioning a unified reporting dashboard built solves many self-service BI problems.
It costs significantly less than creating BI software from scratch, is easy to train on, and makes data more readily usable on a daily basis.
Plus, it can be added onto if another SaaS solution is added to the system.
Digital on a Dime
Business intelligence doesn’t have to be a tool limited to the Fortune 500.
Using these solutions, every company can spread their BI investment out over time and begin seeing results before traditional companies have finished building their servers.
How accessible is your BI data? Concepta builds intuitive, dynamic BI dashboards to put data in the hands of decision-makers. Set up your free consultation today!