We have all done it. We are asked to provide some data-based input in order to facilitate a decision, so we quickly scrape some data from our different tools and data sources and we poor into Excel.
You are only making use of 1% of the potential value of your data. Read on to discover how to make full use your data and to understand why analytics and business intelligence is a clear tactical advantage for organisations.
A number of phases can be identified in the maturity of analytics within an organisation. It is important to identify where you stand as an organisation or as a department within a bigger organisation, so you know where you need to be heading in order to gain more value from your data.
Most analytical activities start with the need of insights for business. Usually the result is a report which is created manually and is ran on a monthly basis. Month after month this requires manual extraction and handling of the data. These activities are labour extensive and therefore cost your organisation a huge amount of money on yearly basis. A first step would be to automate these activities.
In some cases the use of a proper business intelligence tool (think about Power BI, Tableau or a free tool such Google Data Studio) can be enough to have some automated daily reporting. These BI tools offer connectors to some well known databases and other tools which generate data, such as Google Analytics, Google Ads, CRM systems, … In other cases it might be necessary to integrate your data in a central database, data warehouse or data lake, which you can in turn connect to with your business intelligence tool.
The second option is what we usually advise to organisations which have the means for implementing it. A central repository for all you historical data is currently the only way for gaining more value from your data in the long run. In order to move into advanced analytics you need to have easy access to all your data. Furthermore, the availability of historical data is what drives the opportunities for predictive modelling. If we cannot analyse the trends of the past then we cannot predict how these will evolve in the future. And don’t forget. The more historical data you have, the more accurate your correlations and predictions will be.
A central data repository also reduces the risks of data loss. It happens so often that the service of a certain tool is discontinued and replaced by another (think about replacing Webtrends by Google Analytics for your web analytics). Without a proper backup of your data, years of data might get lost.
Once an organisation has mastered their data by automating their reporting and has matured in the use of predictive statistics for decision making, more use cases will present themselves where simple decision making can be automated based on data. In a first phase predictive models become important input towards human decision making. Ultimately, once the models have been refined to the level where it is consistently providing the best next action to take, simple decisions can be fully automated. Think about automating your key word advertising based on months or years of historical campaigns that you ran.
Fast decision making is critical in this era of digitalisation and disruption of industries. Remember that the ultimate goal of analytics and business intelligence is to allow the relevant stakeholders to make informed decisions. As your organisation moves through the maturity phases of analytics, you’ll find yourself making those informed decisions faster and faster. As such, analytics and business intelligence become a tactical advantage for your organisation.
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