The 3 Steps to Do Data Visualisation Right
Data visualisation tools, like Cognos Analytics, Power BI and Tableau, promise the ability to make quick, precise decisions, make accurate forecasts, and discover new insights buried deep in your data. And yet, most organisations fail to meet business objectives with these tools. According to Gartner, the failure rate for new BI initiatives hovers around 70 percent. How is this possible?
This is the last part of our five-part series on data visualisation. In the first article, we looked at the benefits that data visualisation can provide your organisation. Then, we discussed the one data visualisation mistake many organisations make. Lastly, we introduced the different types of data visualisations and how to effectively use them.
In this article, we’re going to zoom out a bit and look at what your organisation can do to make sure you succeed with your next BI initiative. We’ll talk about some of the pitfalls that prevent 70 percent of organisations from succeeding.
Define the Specific Value to Your Business
Successfully implementing a data visualisation strategy starts with defining the specific value you expect it to bring your organisation. There are two reasons for this: first, this gives you a benchmark for determining whether your initiative was a success or failure. Second, it gives you parameters when building out the project.
Most organisations have no problem defining a value. I mean, every blog, webinar, and white paper starts with explaining the need to define an objective and value. That’s because this step is critical to effective and successful implementation of any project.
Broadly defining the value data visualisation will bring your business is where most organisations go wrong. It’s not enough to state that the “value of your data visualisation strategy will allow you to discover insights about your data”. Would you sign off on a project that promised that? I wouldn’t!
From experience, this problem often stems because, at any given time, managers and executives have dozens of issues that they’re trying to solve — retention, profit, distribution, cash flow and more. Plus, it’s easier to get buy-in when we present our initiative as a solution to every ailment within the organisation.
To improve your odds of success, you need to have a specific and concrete definition of value. The more concrete you are, the higher your chance of success because you can align your resources — money, tools, and people — to that single objective.
Some good examples might include:
- Which products do you make money on?
- What customers could you move on to a competitor (yeah, cos they’d love to inherit your loss making customers).
- Where is your cash going?
Or as tighter examples:
- Exploring how age demographics impact product orders.
- Discovering how different channel partners contribute to the overall success of your organisation.
- Accessing the value of a potential acquisition of a company.
Your goal is to start with a single metric and a single problem. Yes, I know it seems too simple and your organisation is running hundreds of metrics. But starting too large is what’s causing most organisations to fail with BI and data visualisation. They try to “boil the ocean” and fail. Start small. Get success. Build on that.
Start by asking yourself, “what is a problem, if solved, would make a significant impact on the organisation?” You have to be really, really good at answering this question. And then sticking to that decision.
Augment Rather Than Replace
When organisations decided to get better at data visualisation and BI, a lot of them start researching new tools and software. It’s easy to believe the reason for your less-than-perfect results is because you didn’t have the right software. If only you had the right plug and play solution, there would be no issue. I think you just heard me call bulls..t on that one.
When starting with a new data visualisation strategy, think about augmenting rather than replacing. Instead, of thinking the tools are the answer and then searching for the “perfect” tool, check out the ones you already have and then, and only then, take a look at other vendors.
There is a good chance that the tools you currently have are sufficient to get the job done. You can look at new solutions as your needs change and after you have demonstrated success. and when you do call us cos we’ll have the right tool to sell you!
Recruit the Right Team
Finding the right people for a new initiative is important. If you clearly defined the value data visualisation will bring your organisation, it becomes easier to discover the skill sets and people you might need for the project.
When we looked at the different data visualisation types, we talked about the skills that are needed. For initiatives that are more discovery-based and deal with multiple or massive data sets, it’s a good idea to find a data scientist or someone with technical skills in big data. But if your goal is to make better graphics to get company buy-in for an initiative, then you might only need a designer.
Finding the right skill set for your project will be an ongoing process. As the needs of your project change, so should your people. You might hire a designer and realise you need a specialist accountant (like us) or data scientist. Or vice versa.
Waiting too long to realise that you need help is the most common mistake I see organisations make when it comes to recruiting the right people. They’re slow to bring on a consultant until the project has all but officially been declared a failure. They’re trying to resuscitate a project that should be declared dead. There is little any consultant can do once it reaches this point — except start over.
Getting started is about starting small. I know that’s a lot easier said than done. You have the CEO and shareholders breathing down your neck demanding better results.
Start small and define a specific value that you want BI and data visualisation to bring your organisation. Then, align the right resources and people to that objective. This will improve your odds of success.
However, no matter how well you plan initially, you will need to adjust as you go along. Don’t be afraid to hire outside help or start over. Throw out the idea that you invested time and money so you might as well keep rolling the ball up the hill. It’s why it pays to start small. Your investments are smaller.
Now I want to hear from you, what specific and concrete value do you expect a BI initiative to bring to your organisation?
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