Trends in knowledge management and reporting in 2023 is influenced by the overall global situation. 2022 was another challenging year, the effects of which are still being felt in the year ahead: the global economy is facing the highest inflation in decades and energy prices are high. Real-time monitoring of price levels is essential to maintain the profitability of a business, and prices and availability of raw materials, for example, are highly volatile.
In the past, knowledge management has sought to answer the questions of what has happened. Now the perspective broadens to diagnose why it happened, and moves from looking at what happened previously to anticipating what will happen in the future. Reporting by an individual organization also seems to follow the cycle described above.
The key trends for knowledge management in 2023 will be data warehousing, automation of data collection and processing, and data enrichment in reporting, including as a basis for machine learning. The introduction of machine learning requires rich and high-quality data, which can be easily obtained from a central repository. Personalized, on-demand reporting is also evolving: the user is able to customize the desired report in a ready-made reporting framework.
Predictive Power BI reporting – what will happen in the future
The key role of predictive analytics is to provide management with the most relevant metrics in a timely manner to enable proactive action.
Adequate historical data of the organization allows the identification of fluctuations, which enables you to prepare for changes in staffing needs or numbers, increasing staff skills or increasing demand for products, among others.
In the manufacturing industry, timely stock reporting is important for forecasting: when the necessary components are available on time, the manufacturing process is efficient, and production is able to meet demand. Sales forecasts and price forecasts for raw materials or components help management increase the number of manufacturing staff in a timely manner as demand for products increases, or to source components when their price is lower.
Low-threshold forecasting is represented by, for example, the rental of recreational equipment: it is dependent on the season and the weather – ski equipment will not be rented if there is no snow at the resort. In the health sector, on the other hand, the flu season is prepared for by increasing staffing levels or balancing the availability of skilled staff with the length of operating queues or the availability of operating rooms.
Low-threshold forecasting can also be used for long-term planning. An organization can plan for the future more effectively when it also follows tacit signals and trends. In practice, long-term planning can mean, for example, anticipating staff retirements and preparing for the recruitment of new staff. Educational institutions, in turn, can use historical data to predict which types of students will graduate on time, and for which students may it take longer to complete their studies. Completing a qualification in the target time is influenced by factors such as student demographics and subject.
1. There is more and more data, and it’s also becoming increasingly complex – data is centralized in data warehouses
Reporting services such as Microsoft Power BI can be connected to multiple data sources. These are typically ERP or HR systems, for example. If an organization has a common data warehouse, data can not only be collected and stored, but also processed and modelled in advance for reporting purposes. Combining data sources allows you to enrich your knowledge.
Preliminary processing of data in the data warehouse also contributes to the creation of machine learning models, and provides additional power for Power BI reporting. Reporting extracts ready-made views from the supply into complex datasets, and summarizes them into a report at the desired level of detail, for example, on a monthly level.
The repository can grow, and new data sources can be integrated as needed. Up-to-date and consistent data immediately improves reporting, but there are other benefits as well: when introducing new software, it can be directly linked to existing data through an interface, rather than having to migrate the data from the old software. The organization’s critical data stays safe and accessible in the data warehouse, and doesn’t get lost as systems change.
2. Automatic data collection and machine learning
The use of machine learning to improve forecasting and its accuracy is growing, and this is reflected in a clear increase in demand. The cornerstone of machine learning is sufficient and good quality data, which lowers the threshold for adopting machine learning, and improves the reliability of statistical inference.
3. Data aggregation from multiple sources towards self-service reporting (Reporting as a Service, on-demand reporting, Self-service)
In 2023, Power BI reporting and data management will definitely also include better use of data, providing tailored services for both individual users and organizations. Tailored reports are just part of this evolutionary path.
Reports can be provided as reporting frameworks, where each user can, with minor changes, work out the desired outcome for their own use. In self-service reporting, the user uses predefined page templates, where they can select axes and metrics from a predefined selection to create a customized report for their own use. The most challenging part – the data model, metrics, calculation and their functionality – is verified in advance, and the layout follows the organization’s visual guidelines.
Traditionally, reports are fully pre-built, and the user can only filter their view by, for example, time period or organization, but the graph data remains the same. The knowledge management trends of 2023 will therefore include increasingly customized report views, and thus more accessible metrics to making decisions about an individual’s work.
Reports are essentially communication
The reports are an efficient communication tool for management, staff, and stakeholders. When presented in a simple and understandable format, and collected and used with the target audience in mind, the data is suitable as is for stakeholder communication, for example to external decision-makers who are not necessarily experts on the subject matter being reported on.
Reports can be easily shared with different stakeholders through access rights, allowing people outside the organization to view reports that are relevant to them. For example, a particular municipality or city can invite the Ministry of Finance to look at its budget reports, or new welfare counties can share information effectively across former organizational boundaries.
For reports to truly serve their intended purpose – to help monitor and make decisions about essential activities and changes in an organization – the path from data collection to the end user’s screen must be carefully considered. This fact will not go out of fashion, but will continue to be the dominant trend in knowledge management in 2023.
With Pinja, your organization’s Power BI reporting is efficient and timely.
Read more:
Pinja guides you from searching for information to knowledge management – regardless of the industry
User-centric reporting is an effective way to communicate
Machine learning significantly improves the accuracy of business forecasts
