Decision Inc's Kate McFarlane: AI and machine learning will make your reporting responsive to changing conditions.
Without data, a company cannot grow. It is as much a part of the success of any organisation as the tools, processes, systems, and people required to develop products and services in a competitive market. As part of this, reports become an invaluable asset that extends beyond simply ticking the financial boxes. Instead, these transform a business by not only enabling it to better understand its data, but also the value it has for success.
But for this to work, the reporting strategy must evolve from being reactive into something that is more proactive and accounts for the real-time feedback of customers and continually evolving market conditions. This is where the likes of predictive analytics, machine learning (ML) and artificial intelligence (AI) technologies can enhance the decision-making process. These sophisticated technologies are designed to integrate with existing processes to deliver even more value from the data at hand.
Business intelligence and customer relationship management are not the buzzwords of the past. Instead, these have become integrated into every process across business units with reporting as the foundation. By learning from existing information, and guided by the experience of employees, ML can automate many of the previously manual-intensive processes. This will enable employees to focus more of their efforts on delivering higher cognitive value to the business and help the organisation better meet their strategic objectives.
Getting started
Moreover, decision-makers must make a concerted effort to embrace this more agile environment. There is no ideal time to get started. Data will never be completely clean to make frictionless analysis possible. It is important to forge ahead, identify analytics as a key business strategy, and start by exposing the data.
The business must move through an iterative and agile process, refining its analytical capability, and ensure that each iteration adds value to the organisation and builds trust with the business users.
Reporting and analytics can track performance to better enable management to gauge the success or failures of any initiative, product, or service. This access must also filter down to the relevant supporting teams and provide them with access to the relevant business information. Reports must have consistent data lineage and be presented in a user-friendly manner to facilitate understanding the values inherent to the organisation.
As the organisation grows in analytical maturity, the ability to use advanced analytical calculations and scenario modelling effectively becomes possible.
Data journey
The journey from data to decision-making through reporting is a complex one. It requires a concerted effort to align operations. From there, the company must account for its information needs. This means data must be customer- and product-focused as well as factor in the operational efficiency required to grow the business.
Analysis must also incorporate aspects such as data availability, its accuracy and granularity, historical requirements, and the ability to link between data sets. For example, if data is not kept up to date, then effective decision-making is hampered and will not be reflective of current market requirements.
Another important consideration is the frequency of information availability. Reporting timelines can help guide this and link to the decision-making expectations from leadership. Having the best data in the world means very little if management cannot access it when they need it. And if they do not have the skills on hand to analyse it, the reports by themselves mean very little.
This therefore requires information to be presented in a manner that takes the user experience into account. The automated distribution of dashboards and operational reports will encourage users to access the information in a timely manner and make the adoption a far smoother process.
Finally, change management is a fundamental activity and must include user data literacy and toolset training and support on the reporting process journey. All told, the reporting process changes significantly once the value of data is understood and innovative technologies are harnessed to aid decision-making.
There is no quick fix to accomplish this, however. But once there is organisational intent to re-evaluate the reporting strategy and the value derived from data, then growth is made possible.
