Published 13. Feb. 2017
Think Big, Start Small. But Do Start!
Innovation with data analytics.
Innovation is at the top of the agenda for many organisations. And with good reason. In addition to the optimisation of existing activities, the development of new growth opportunities is necessary to stay ahead of the competition. Smart use of data (analytics) is crucial for achieving these business objectives. That is why managers pay a lot of attention to big data and analytics. However, it is difficult to concretely define these advantages. Big Data is a major undertaking for many but is often seen as a vague term. What exactly does it mean? Everyone seems to be enthusiastic about it, but at the same time the precise starting and end points still need to be determined. In this situation, the old adage ‘Think Big, Act Small’ certainly applies.
Something with big data or data science, please
Organisations that want to do ‘something’ with data analytics usually ask two questions: ‘We have this data but what can we do with it?’ and ‘We want to start using Big Data, which tools do you recommend?’. The answer to both questions is a counter-question: Why do you want to know this?/What do you want to achieve? After all, making an investment only makes sense if there is a specific challenge or project at hand. The more specific the challenge or project, the greater the chance of a successful project. You cannot determine whether data will help you find a solution or which tools are needed until you have a clear starting This isn’t skepticism, but rather an approach that highlights the importance of data analytics for organisations. That is because it isn’t about technology and methodologies, it’s about contributing to the actual solution to an organisational problem. Only in this context does using data analytics make sense.
The well-known examples of successful innovators such as Airbnb and Uber emphasize this approach. Of course data is an important part of their success, but it wasn’t their starting point. These two organisations first sought a solution to customer problems. And although they used the latest data analytics technologies, the first versions of their product were relatively simple and data science played a limited role in the process.
The most important question that remains is: So how should we go about this? Many organisations do have a dataset in mind as well as (usually) a focus area. For example, machine data and some sort of content optimisation. Or sales data and something like increasing revenue. Unfortunately, there are no generic data analytics solutions that will immediately give you the desired result. That is why it’s useful to take a step back and define a specific solution with a good business case based on these starting points.
The search for a solution to a specific business problem starts at the Datalab. Together with the organisation, data scientists examine the focus area and the available data. In addition to knowledge of analytics and IT skills, these scientists also provide a dose of creativity and inquisitive thinking. Most often, this combination quickly gives rise to a specific idea. The Datalab is absolutely not a theoretical exercise. The available and usable data is analysed and the results are presented in visual format. This forms the basis for new insights and is the foundation for a working prototype used to bring solutions to life. It’s only once the solution has been specified, has been understood by everyone and has a healthy business case, that a project is started in order to integrate the solution into daily processes. Then questions about the required tools become relevant. Entrenchment in the organisation is a crucial step because ideas and algorithms don’t create value until they’ve been implemented.
It’s evident that data analytics can help organisations achieve their innovation goals. This is why, by definition, it makes sense to take on this challenge. It’s scary, but you should do it. Don’t get hung up as an organisation on the ‘Think Big’ part on account of the ‘we are not ready for this’ notion. Simply start with a small but specific project and continue taking steps towards your goal with small projects. Don’t be afraid that there isn’t enough data or that the data isn’t correct. Take on the challenge. Take advantage of opportunities, keep your projects small and above all don’t forget to start.
Axians will be attending Data and Analytics in the Netherlands on the 8th of March 2017 as a solution provider. Event discussions include:
- The Opportunities of Collective Intelligence – How can it be transformed into commercial added value?
- The Life Cycle of Data – Insights on the right moment.
- Advanced Analytics – Matching business and method.
- How far does your responsibility go in Data Analytics ethics?
- Organizational Structure – Embedding a data driven mindset.