Predictive analytics is helping many businesses to create more accurate forecasts and uncover new solutions to business problems based on historical data.
This is just one facet of data analysis, though. The rapid advance of technology has turned data and analytics from a niche to an established field that enables businesses to stay agile, reshape their activities and make better decisions.
Many small to medium businesses are yet to unlock the full potential of data and analytics but the maturity and complexity of an organisation are of little matter. Regardless of what stage a business is at, leveraging data can help drive competitive advantage.
Although trying to predict the future isn’t easy, where do business owners start? To take the first step on the data journey, there needs to be a destination.
How data solves key business problems
Aligning change and innovation initiatives with the business strategy is critical to their success, and data and analytics projects are no exception.
Business owners must start by listing and prioritising the key business objectives and challenges their organisations are facing, such as:
- Growing the company’s presence in a certain market.
- Optimising their marketing spend.
- Improving customer experience.
- Identifying parameters around breakeven.
For each, identifying the source of information that would be useful in making decisions and solving them is critical. It could be data already used in spreadsheet analysis, data that has been generated and stored in another tool or system, or external data.
Those business challenges deemed critical for which rich and relevant datasets have been identified should be considered as data and analytics priorities. It is useful to develop a value versus complexity prioritisation model that can assist with this task.
Collecting and centralising data
Pooling collected data in a central location allows for agility and responsiveness in decision making.
Centralising data assets is completed through a data lake, a repository for structured and unstructured data that is stored in a secure cloud location to allow scalability. Data lakes have been shown to increase operational efficiency.
This structure guarantees ownership, control, and accessibility of your data without restrictions and enables concurrent analysis of information collected from multiple sources.
Not every piece of data collected may be relevant to the identified problems at the time of collection, but it may be useful in future. As greater amounts of data are collected, more detailed insight can be drawn from it or it can be used to refine other parcels of information.
Leveraging your new data infrastructure
Once up and running, the data in the lake can be further cleansed, analysed and modelled to generate insights tailored to address the identified problems and challenges.
Data and analytics are often associated with advanced artificial intelligence applications, such as computer vision. However, less complicated solutions such as automated reporting can be equally as valuable to a business and reasonably simple to implement.
Information in the cloud can be queried on demand and insights displayed through Business Intelligence dashboards or embedded in existing tools or reports.
Initial dashboards can be very simple, and as new questions emerge across the business, solutions can be designed to address these needs. These solutions will allow your business to make better decisions grounded in:
- Timely information.
- A single source of truth.
- Enhanced reports including new metrics.
- New insights and forecasts uncovered using machine learning algorithms.
The value of data comes from staying ahead of the curve to win customers and clients, tapping into new markets and predicting where the next opportunity may come from. With real-time information at their fingertips, business owners can make timely and informed decisions that drive efficiency and growth.
Sudha Viswanathan and Francois Ehly, Pitcher Partners Melbourne
