But getting the right data, and ensuring you can derive the best insight from it is no easy task. In fact, according to Gartner, only one in five business analytics insights will result in positive business outcomes.
There are a number of reasons why this might be the case. Some of them will be technical, such as using the wrong software tools. Some will be down to company culture, or issues with communication between departments.
But whatever the underlying cause, the results will be the same; poor insights that don't produce the desired results, and unhappy executives who have to sign the checks. Therefore, tackling the issues needs to be the priority for any BI strategy. And the first step is recognizing what's going wrong.
With this in mind, here are seven key issues you need to be on the lookout for that could be causing your BI strategy to fall apart.
1. You're still using legacy technology
The volume of data generated by businesses over the last few years has skyrocketed. Research from Cisco, for example, forecasts that global IP traffic will increase threefold over the next five years, but if you're still using the same systems you'd had in place for years, the odds are you won't be able to cope with this.
A lack of capacity is one of the most common reasons for a BI project failing, and this can often be traced to technology that's outdated or poorly suited to the specific demands of your business, such as tools that can't offer real-time results. There are a wealth of sophisticated BI options available now, so it's important you do your research and identify those that will be the best fit for your needs, rather than choosing based on brand recognition.
2. You don't have the right skills
However, replacing legacy tools with the latest technology will be of no use unless you have the right skills in your BI team to make the most of it. While expertise in tools such as Tableau and SQL are a must, you also need people that will be able to look at raw data and consider how it can be best applied to your business.
Data analysis, problem solving and attention to detail are just some of the skills you need within your team, but it's important not to overlook softer skills such as communication. If you aren't able to adequately explain your findings to business units, you won’t be able to reap the benefits of your work.
3. Your goals are unclear or unrealistic
Effective BI tools are frequently sold to other departments as a panacea for any issues a business has, with the potential to offer a transformation in how firms make decisions. However, this can lead to IT teams overpromising on what they can provide, which can lead to disillusionment if the results aren't as revolutionary as expected.
At the same time, business units can cause problems by setting goals that are too vague, or outside the scope of your capabilities. BI teams should take care to ensure they aren't merely acting as 'order takers' for the rest of the business, as it may often be the case that non-technical employees won't fully understand what they're asking for, or if their requests are feasible. It's important to manage expectations and work with other departments to devise briefs that are clear, specific and accurate.
4. You're looking at the wrong analytics
Firms will be dealing with a huge volume of data in their BI strategies, so it's vital you're able to narrow this down and focus only on the pieces that will be most relevant to you. However, even if you’re able to separate the signal from the noise, you need to be certain that the analytics you're performing will have useful implications for the business.
It can be easy for professionals to get tunnel vision and spend their time on areas that may be interesting, but are academic when it comes to providing value to the business. Ask yourself how the analysis will help the company meet its goals, and if there's no immediate and obvious answer, turn your attention elsewhere.
5. You're too focused on the data itself
It may seem counter intuitive, but data analytics itself is only a small part of a successful BI strategy. Frequently, failures occur because the results of these analytics operations aren’t presented in the right way, or no explanations are given for the recommended courses of action.
You can't expect to present non-skilled departments with a list of numbers and expect them to figure out what they mean. For skilled IT professionals, it may be obvious what certain data points are telling them, but this won’t be the case for many executives. Therefore, you need to tell a compelling story to business units and translate the data into real-world terms if your insights are to be acted on effectively.
6. Your platform is too hard to use
There are a range of powerful data analysis tools businesses can employ to assist with their BI strategies, but if these are too complicated or too unintuitive to use, people within the business will be loath to embrace them. According to BI Scorecard, adoption rates for BI tools sit at around 22%, and poor user experiences will be one key reason for this.
Insights gained from analytics need to be clear and easy to understand. This is often interpreted to mean 'visual', but charts and graphs won’t always be the best way of presenting information. It's therefore important you talk to end-users to find out which metrics are of most value and how these should be presented. Know when to use what format and you'll find it a lot easier to keep people interested.
7. You don't have the right support
Like any IT project, a BI strategy can only get results if everyone involved is bought into the approach and has confidence it will be able to deliver. If business units don't see the value in your work, or express skepticism of your findings, they're much less likely to put recommendations into practice.
Therefore, it’s vital that BI operations have the support of senior personnel, both within the IT department and at board level. It will take time and resources to get a BI strategy up and running, and having C-level personnel in your corner is vital in ensuring it doesn't get abandoned before it has a chance to show results.
- A Quick Introduction to the Modern Analytics Journey
- The Convergence of Analytics, Data Science and Process Automation
- The Top 10 Things to Look for in an Analytic Process Automation Platform
- The 4 Principles of Analytic Process Automation
The thrill of solving
Alteryx unleashes the power of data analytics to help people everywhere solve business and societal problems. Because we believe #TogetherWeSolve. As a global leader in analytic process automation (APA), Alteryx unifies analytics, data science and business process automation in one, end-to-end platform to accelerate digital transformation. Organizations of all sizes, all over the world, rely on the Alteryx Analytic Process Automation Platform to deliver high-impact business outcomes and the rapid upskilling of their modern workforce.
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