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The Future of Reporting

How To Modernize and Optimize Your Enterprise Reporting

Recent years have seen extensive interest in topics around explorative BI such as advanced and predictive analytics. Modernizing and optimizing enterprise reporting – or classical BI – has not been such a priority for many of today’s organizations, even though it constitutes the backbone of information supply for decision support. It is an increasing challenge for organizations to deliver high quality yet more flexible reporting solutions and applications in less time.

Many reporting systems today are failing to provide adequate support to users while much of the content created is unused or lacks relevance to the most important business questions. Building and maintaining traditional solutions is expensive and fails to satisfy users in many cases. Today’s data-literate users want governed and scalable self-service BI functions to answer critical business questions and to get the most out of their data assets.

Technological innovations and their increasing proliferation are shaping enterprise reporting and Business Intelligence. Most prominently, machine learning (ML) enables improvements in various fields. It allows new forms of consumption and interaction with BI content through natural language queries (NLQ) run through chat-bots and other conversational interfaces on any device. ML allows non-statisticians to leverage advanced and predictive analytics to detect hidden patterns and correlations in data, increasing the depth of analyses conducted. 

Natural language generation (NLG), again powered by ML, supports users in understanding patterns and explains causing factors. ML helps users prepare data to enhance reports and to select appropriate data visualizations in visual analysis and dashboards. Cloud, with containerization, APIs, microservices and mobile have been hot topics in BI for some time now. 

Their elevated level of maturity makes them attractive for an increasing number of existing solutions. The mix of these and further developments creates attractive architecture options and significantly extends the reach of reporting and Business Intelligence beyond the borders of internal deployments. 

Modernizing and optimizing enterprise reporting applications to support shifting and increasing demands is vital to continuously deliver trusted information for decision support in rapidly changing environments. 

Modernizing Enterprise Reporting To Meet Changing Needs

Only a minority of companies say they have a modern reporting landscape and regularly base decisions on data. In fact, most companies struggle with data-related problems, organizational issues or outdated business intelligence and data analytics infrastructures which ignore more current usage scenarios such as explorative analytics on big data sources.

These problems become even more obvious when contrasted with modern infrastructures built in the cloud and micro services as well as the challenges caused by exploding data volume and variety.

Finally, the greatest pressure comes from competition. Companies must react quicker than ever to changing demands from their customers to keep pace with their competition. The time has come to modernize today’s reporting landscapes and base decisions on information rather than gut-feeling – the legacy of the past must be overcome to reach the future of reporting.

The BARC survey ‘The Future of Reporting’ is based on a survey of over 600 participants worldwide from 58 countries across a range of industries.

Flexibility In Information Usage And Personalization Are The Key To The Future Of Reporting

Although a common data model consisting of aligned structures and measures is needed for consistency and data governance, it will not grant business departments the freedom required to efficiently analyze and interpret data. Architectures and modern tools which enable business users to search, prepare and analyze data will pave the way to reacting promptly to market changes.

Business users who consume predefined content require greater flexibility in data navigation as well as personalized content distributed over a vast number of different channels.

Modern Reporting Tools Must Focus On Business Users

Business users will be the major creators of reports and content in the future. They require intuitive and modern tools which can support them in data analysis and report creation tasks. Technologies to increase automation and efficiency such as machine learning help users to speed up their work.

Increasing reuse of content powered by device-agnostic creation prevents report explosion even in large and decentralized environments.

Fact-Based Decision-Making Requires Trusted And Managed Data

Data management has always been a challenge for companies. The most prominent challenge is to overcome multiple and conflicting definitions for KPIs, which is typically addressed with rigid and strongly centralized control. Data quality is seldomly handled in source systems in a way that meets the needs of decision support.

As the number of sources, volume and variety of data increase, data-related issues are felt more strongly. Therefore, state-of-the-art and future-proof architecture concepts and tools are needed to deal with these challenges.

Inspiring Action From Data Is The Holy Grail Of Reporting And Business Intelligence

Managers are a key element in establishing data-based decision-making as the new norm in their organizations. All employees need appropriately prepared information that is easy to retrieve and to grasp. Laggards in particular must catch up on regularly supplying their management and operational staff with relevant information.

BARC Recommendation

Gleaned from BARC’s experience in the market and results from this survey, we offer you recommendations to improve your enterprise reporting and BI to the next level.

Improve customer orientation through modern technology

Improving customer orientation is a mantra for many companies. The customers of enterprise reporting and BI are its consumer. Therefore, consumer orientation is the single most effective lever you have, to improve the benefits gained from BI. 

Implement modern tools with intuitive interfaces to simplify content consumption and creation, allowing more employees to analyze data for relevant patterns and trends to inform their decisions. Make sure content is easy to understand and retrieve for everyone, make sure it can be consumed anywhere. 

Mobile BI apps are supported by most Business intelligence tools, yet they are not used pervasively. This will and must change. With this, we will see a shift in consumer expectations towards more interactive yet guided apps available everywhere.

Natural language search and queries make BI easy to retrieve and accessible to everyone. The combination of NLQ and mobile BI is even more powerful and opens new ways of interaction. Deploy NLQ and mobile BI to equip every employee with actionable insights everywhere. 

Easier access and  consumption lead to higher information use. Higher use leads to greater benefits and greater benefits lead to higher use.

Modernize data management to guarantee high data quality

The increasing number of sources to integrate as well as growing volume and variety are the top challenge for enterprise reporting today and will continue to grow in the future. Modernize your data management to cope with this challenge and to address insufficient data quality in source systems as well as rising expectations from business users. Applying state-of-the-art technology and processes to ingest, integrate and distribute data is the approach pursued by most companies today to stay ahead of increasing requirements.

It is crucial to simplify data consumption and access for all users to support self-service requirements. Maintain a comprehensive data catalog to make data treasures easy to find. Linking data to business metadata is crucial for data governance. Leverage the power of the user community and collaboration to describe data assets and comment on the data’s use and usefulness.

Help all employees to level-up their data skills and to collaborate

There is a lot to gain from reporting and BI if all business users can use data to inform their decisions. Educate and support business users to increase their data literacy and equip them with increasingly valuable skills.

Educate your IT and BICC so they can fully occupy their new roles in governed self-service environments. Their focus will shift from development-oriented tasks to consulting and supporting business users, from building reports to curating data.

Deploy self-service and accompanying governance measures

Leaders trust in the advantages of self-service BI. They already offer self-service capabilities like ad hoc analyses and reports more often than others. Nevertheless, their number one initiative to enhance their enterprise reporting is deploying self-service capabilities to more users. The same should be true for your future reporting and BI landscape.

Governed self-service BI is the key to gleaning relevant and timely insights from data– connected and integrated. Only pervasive standards guarantee a stable foundation for collaboration and content reuse, making Business Intelligence efficient and more effective.

Decentralize content creation to support data-driven decision-making in every corner of your organization. Emphasize data governance measures and deploy tools that support decentralized BI built on a stable foundation.

Management must promote data-driven decisions

If more decisions are based on data, the importance of managers paradoxically grows. It is the managers who must demonstrate every day that facts trump opinions – even if it is their own opinion.

Managers must be aware of their duty to open the space for discussions based on data to inform decisions. This will include more employees in decision-making and will ultimate lead to better decisions – for the benefit of the whole organization.

Static infographic of the key findings

Download the full study here.

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Market Research Analyst

Annika conducts both product-based and topic-based BARC studies in the areas of BI & analytics, data management and corporate performance management.

As project manager, she is responsible for time and resource planning and oversees projects from questionnaire creation to publication.

Depending on the study, she also handles the implementation of project steps such as questionnaire design, field phase control, data preparation and analysis.

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