In a world that is increasingly driven by technology and data, the pace of change is rapid and many organisations are struggling to keep up.
Data Analytics is changing the business landscape, the volume of data available and transactions has expanded massively over the last ten years. While running your operations more efficiently is the key to maintaining profits and competitive advantage, data is getting ‘bigger,’ the problems seem more complicated and the solutions harder to find.
The recently published National Analytics Maturity Study 2018 reveals that 42% of Irish organisations agreed that the application of data analytics technology would streamline internal operations.
Creating efficient operations requires good management and even better decision making but 56% of organisations report having a culture of decision making based on intuition rather than on data.
Data and analytics can enable an organisation to leverage its own investment in systems and data to drive better decisions. AI and Machine learning can help improve predictions and forecasts and Robotic Process Automation (RPA) can help streamline business processes.
Most organisations have digital capabilities in different pockets but are a long way from infusing digital where it needs to be, across the entire business. I’ve distilled some of the key learnings from my experience of working with clients here.
Don’t build a solution without knowing the problem
The study shows that clearly defining the business problem is the #1 component to making analytics projects work well. Start small and remember you can achieve a lot with less. Choose a business problem, source the data, experiment and prototype. Once you have proved the value of analytics, iterate and expand the scope.
Have a clear strategy in place
Many organisations have failed to implement a data and analytics strategy by treating it as an IT project. This is often an expensive mistake, which can leave management nervous to try again. Don’t treat it as a technology pet project – that’s only one aspect of it – it’s important for organisations to have a clear strategy in implementing tech and analytics into their business. The study reports that 60% of organisations feel that they lack the budget and organisational commitment for a data analytics project.
The robots are your friends
Artificial Intelligence and Machine Learning are not just emerging, they are solving real business problems today! These technologies are effectively reducing the cost of prediction for organisations.
RPA can free up staff to focus on more value add activities, eliminating operational errors, workflow delays and repetitive manual tasks with data-driven behaviour improving efficiency and reliability.
Embrace the cloud
Explore cloud and open source to accelerate experimentation and implementation of analytics. Cloud is secure, scalable and has significant cost benefits.
Don’t forget the human element
Projects can fail because they’ve taken a technology focus but failed to identify the human element of integrating it into the business. Technology must sit where insight is required and decisions are made. The most successful implementations combine functional expertise with technology.
The National Analytics Maturity Study 2018 shows that 79% of organisations have difficulty in recruiting staff with deep analytics skills. With a good career framework and structured training you can upskill existing staff with the required data and analytics expertise.
Don’t let data quality be a barrier
Many organisations let messy data from multiple sources hold back the implementation of analytics. Self-service BI and visualisation tools will help build momentum, surface data quality issues and actually drive better data governance.
Perhaps the most important lesson I’ve learned when it comes to implementing analytics and emerging technologies is don’t be afraid to try. Encourage people in your organisation to learn about these technologies, embrace them, pick a business problem and try and resolve it, the cost of failure is small compared to what you will learn.
