When new software is developed, whether a simple app or something more involved, it should always be a data-driven process. Business intelligence, or BI, is the process whereby internal teams and stakeholders work with analysts to determine the most effective ways to solve problems.
This sounds like a sensible approach, and ultimately whether a company is going through a digital transformation or simply needs new software, the role of analysts and intelligence is about solving problems.
Digital transformation powered by business intelligence has a tremendous potential for making faster, better-informed decisions and accelerating business growth.
However, too many businesses have struggled with digital transformation projects. Whether or not they've worked with an analyst. Or companies have worked with IT consultants. Clients either have negative experiences, or see a consultant that sets a crazy rate, then ultimately achieves nothing except writing lots of reports that have no positive long-term impact.
Why business intelligence is important?
What is the purpose of business intelligence in a business?
The purpose of business intelligence is to help business owners, managers and exacutives find the right solutions to business problems through collecting relevant data and transforming it into meaningful, actionable insight.
In our experience, and this an experience common across the sector, business don't always know what they need.
Businesses are clear that there is a problem. Or a series of problems. Challenges that need solving. But, expressing and even understanding these problems is a challenge in itself.
At the same time, IT and software teams — whether internal or external — can struggle to understand these problems, and then turn those around into a workable solution. Equally, for an IT team to translate the solution into something business customers and users understand, isn't always easy either. It usually doesn't matter what that solution is.
From software and apps to a re-platforming, to new hardware. There are many solutions on the market, but those aren't worth very much unless a problem is clearly defined and the right solution put in place to solve it.
This disconnect between problems and solutions is why businesses need an intelligent, data-driven approach to uncovering the right questions and answers. Hence the value of business intelligence, otherwise companies get software created that isn't right for the problem they were having. New software and digital transformation initiative can turn into a massive waste of money, and a headache, which can undermine confidence in IT and the value it can generate.
What is business intelligence (BI)?
Now we understand the value of BI, it would be useful to know what business intelligence (BI) is.
Although there is BI software, we are going to focus on BI as a process. However, that doesn't mean that software doesn't play a role in BI as a process. Often, whether companies are using custom business intelligence software dashboard, or even having one developed, or an analyst uses a suite of BI solutions during a digital transformation consultation, these are only a means to an end.
The objective, with any business intelligence analysis process, should be to come away with the following:
A detailed problem analysis. Starting at a high level, and then zooming in to a micro/user-centric analysis of the challenges a company is facing. This could be anything from an outdated process, to the need to overhaul or completely replace a system that is preventing a business from achieving its goals.
Project goals. Now that a company is clear on the problems that need solutions, there should be a set of goals for every project. What are the expected outcomes? What ROI does a company want to achieve with a new IT project?
A solution specification. Once the problem, or series of challenges has been identified, the solution needs a specification. Getting this right as a result of an intelligence-led approach avoids misunderstandings and keeps projects on time and in budget once work commence. In a specification, end-users, decision makers and budget holders should have a clear idea what and why a product is going to achieve. None of it should be a mystery. Every feature and aspect of an app, or another type of solution, should be tied to a business case and provide an operational answer to a problem internal or external customers or stakeholders are having.
A project roadmap. Once the specifications detail the solution that needs to be developed, both parties need to agree a roadmap. Like a specification, if this isn’t mapped out before work starts it can cause serious problems down the road.
For businesses who've not gone through this sort of process in the past, this might sound like a lot of work. But avoiding it, or skipping through these stages too quickly causes more problems than it solves.
Skipping this process often means overlooking user input. Putting together a spec that doesn't answer every question. Failing to gather enough data before deciding what is and isn't relevant. Without data, a software specification is only a fragmented set of ideas. Without real-world user input and feedback loops, a new application isn't going to address the needs of real users.
Companies end up commissioning software based on half-baked analysis, which usually results in software being developed too quickly, that doesn't solve every problem. This can cause chaos. New ideas filter in, expanding a project scope piecemeal, resulting in delays, budget overruns, and end result that doesn't make anyone happy, and ultimately doesn't achieve the goals.
How does business intelligence (BI) work in practice?
For examples sake, let’s say a company uses legacy software for a key internal process. No one likes using this software. The company has been wanting to replace it for a while. Now there is a budget and options are being explored.
To achieve the best results, how should a company find a solution?
A) commission a new piece of software, and put it out to tender;
B) engage the end-users first, and review the processes, and explore this with an internal team or software partner before commissioning the work.
B is the most sensible approach. But as too many go with A, it might explain why so many software projects end up over-budget, taking too much time, and either with too many features or the wrong ones.
In practice, going that route depends on every companies processes, systems, and the interplay between the two. An analysis process should examine everything and help you answer the following questions:
- Do the systems we have help your team do their jobs?
- Do they hold them back?
- What features would make the work easier?
- How can we improve processes to positively impact the systems they use?
- How do our systems impact other stakeholders, and customers?
- What efficiencies could be made that could improve workloads and the customer experience?
When developing new systems, data is just as useful as user feedback. A combination of both is needed to map out the most effective solution. Analytics and feedback loops should be put in place to collect the data and user-experiences, and with this information, a project spec, goals, and a roadmap can be created. Once that is done, it should be clear the valuable role business intelligence can play in software development projects.