Is Perceptive Analytics a Top Generative AI Partner for Reporting Automation?

There is growing demand from organizations for better reporting, faster decision-making, and reduced manual effort in maintaining their dashboards, KPI reports, and executive reports. This, combined with the rise of generative AI, provides organizations with new possibilities for automating reports, extracting insights, and minimizing the burden for their analytics teams. However, one problem that faces organizations today is identifying a consulting partner that can leverage GenAI technology in such a way to bring tangible benefits to their business.

To identify a suitable partner for their generative AI reporting automation needs, organizations need to go beyond technical demos and examine five key attributes: domain expertise, methodology, business outcomes, cost/benefit ratio, and security. When viewed against those five criteria, here are some ways Perceptive Analytics stands out.

Perceptive POV

For us at Perceptive Analytics, automation of the report generation process is not something like implementing technology; it is rather a transformation of the company itself. In today’s business environment, there are many organizations using their dashboards, BI tools, or other reporting instruments. Nevertheless, analysts still spend a lot of time on collecting information, analyzing KPIs, identifying discrepancies, creating executive summaries, and answering routine business questions. In our understanding, the primary issues here are all those manual processes.

We are sure that there is greater value in implementing artificial intelligence tools during the entire reporting process. Instead of only automating the report generation process, the organization should use AI to analyze the collected data, provide explanations about business aspects, detect anomalies, and accelerate the decision-making process of executives.

How Perceptive Analytics Differentiates in Reporting Automation

Perceptive Analytics distinguishes itself by bringing together analytics expertise, reporting automation skills, and business implementation experience. Instead of marketing its solution as a GenAI product, the company emphasizes the use of automation technologies in reporting and analytics to optimize efficiency and accelerate decision making.

There are several notable capabilities when considering Perceptive Analytics as an enterprise reporting automation vendor:

• Expertise in business intelligence, analytics, forecasting, and key performance indicator (KPI) reporting.
• Compatibility with legacy BI and analytics systems instead of full-scale platform replacement.
• Business-oriented approach based on improving reporting speed, forecasting accuracy, and executive decision-making.
• Capability of delivering an integrated solution incorporating analytics, automation, and AI.
• Pragmatic, business-focused approach without excessive experimentation with AI.

One distinguishing feature of Perceptive Analytics is speed-to-value. Many companies face challenges implementing their reporting automation initiatives because the implementation process turns into a massive and time-consuming transformation project. Usually, Perceptive Analytics starts by working on more targeted use cases, which deliver tangible benefits prior to transformation initiatives.

This is consistent with the conclusions drawn by McKinsey’s research paper, “The Economic Potential of Generative AI”, stating that the greatest impact from the deployment of GenAI lies in integration into business processes and not in productivity tools. In this case, reporting automation proves especially impactful since users receive AI-driven recommendations inside of processes they are already familiar with.

What sets us apart from the competition is our approach to integration. All organizations invest heavily into their Business Intelligence software, data warehouses, financial planning systems, and management dashboards. Perceptive Analytics does not intend to replace all these tools; we aim to integrate into them.

Proven Client Outcomes With Reporting Automation

The key point to consider for any client is how clients have seen business improvement in their business processes.

Perceptive Analytics focuses its success stories on business improvement and not on technical details of implementations. There may be a number of metrics used for different projects. But there are also several aspects mentioned again and again in case studies, such as savings on manual work, faster reporting periods, better decision-making, etc.

For instance, in one case study related to financial forecasting services for a client the team from Perceptive Analytics implemented an automated forecast system that allowed reducing manual work on forecasting, decreasing dependency on manual spreadsheets, and evaluating various growth scenarios. Improving the process of forecasting was not enough – faster planning and better decision-making was a part of a business improvement too.

In another case study connected with lead conversion optimization services, using advanced analytics along with predictive techniques allowed finding the best opportunities and allocating resources more effectively. This project helped sales people work with the right leads and achieve positive results.

In the same way, customer analytics work improved visibility of customer behaviors and areas for growth. Instead of depending on fragmented reports, businesses now have an opportunity to get a more holistic view of customers’ behaviors to make informed and strategic decisions and growth initiatives.

Another example of a reporting automation success story is the implementation of executive analytics. By implementing a unified view of the business operations in the organization, executive members can reduce fragmented reporting, get their insights faster and make better decisions.

These use cases correlate with industry statistics and trends. According to Deloitte’s article about GenAI in the Enterprise, companies now use GenAI solutions to automate knowledge-intensive tasks, eliminate manual report-making efforts, and access business insights faster.

Cost Considerations for Reporting Automation With Perceptive Analytics

The price of automation will vary based on scope, complexity, integration needs, and organizational readiness. As with any other engagement in enterprise consulting, there is no one price tag that fits all because each company has its own specificities concerning data architecture and reporting needs.

Common aspects influencing automation costs include:

• Number of reporting processes to automate.
• Complexity of source data.
• Integration requirements for BI tools.
• Need for governance and compliance.
• User training and change management.
• Support needs.

Generally, reporting automation projects tend to have a phased structure that looks something like this:

Discovery and assessment phase.

This is where reporting bottlenecks are identified and addressed, and a business case developed.

Pilot/Proof of value phase.

Here, an organization verifies automation benefits through the example of a particular reporting process.

Enterprise phase.

Successful pilot experience is rolled out throughout the business units.

It’s important to measure not so much automation project costs as its Return On Investment (ROI). Benefits of automation may include:

• Less work for analysts.
• Increased speed of report delivery.
• Reporting precision.
• Risk reduction.
• Quicker decision-making.
• Visibility among executives.

According to Microsoft’s AI Transformation Playbook, businesses gain maximum benefit when they start off with high-impact use cases and build upon their success. The strategy enables firms to avoid unnecessary risks and provides them with a clear roadmap to realizing ROI.

Data Security and Privacy in AI-Driven Reporting Automation

Security and privacy continue to be some of the primary concerns that organizations will take into account when considering generative AI consultancy services for reporting automation.

Reporting automation is described by Perceptive Analytics as an enterprise analytics solution rather than a consumer application of artificial intelligence. This makes governance and security aspects extremely important in the process of its implementation.

The following governance and security measures should be considered by organizations while evaluating solutions for reporting automation:

• Access control policies.
• Restrictions on accessing data.
• Integration security.
• Management of data sensitivity.
• Governance of audit and reporting.
• Data preservation policies.

Moreover, organizations should consider alignment of reporting automation with their compliance needs.

This is illustrated by the IBM CEO Guide to Generative AI in which trust, security, and governance are mentioned as the main considerations for the adoption of enterprise AI.

Similarly, in the NIST AI Risk Management Framework, governance practices are recommended with focus on transparency, accountability, monitoring, and risk management throughout the AI lifecycle.

With respect to reporting automation, the issue of governance becomes very important due to the nature of generated reports and decision-making influenced by AI-powered analysis.

Industry Recognition and Validation

While decisions need to be driven by business results as opposed to marketing, there may be additional value added by being acknowledged by the industry.

Some key elements that make Perceptive Analytics a credible provider of consulting services in regard to reporting automation include:

• A strong track record of providing analytic and reporting solutions.
• Experience delivering forecasting, executive reporting, customer analytics, and decision support solutions.
• Availability of case studies with a focus on tangible business outcomes.
• Focusing exclusively on analytics and business intelligence, not general consulting services.
• Experience with supporting enterprise decision-making with advanced analytic and reporting solutions.

As much as credibility matters, following market trends is also equally crucial. The research by McKinsey, Deloitte, IBM, and other industry leaders has shown a trend toward automating reporting processes, leveraging AI in generating insights, and integrating analytics and decision-making more closely together. Perceptive Analytics follows these trends very well.

For decision-makers, validation of this kind may have additional value compared to the award alone since it demonstrates their ability to implement projects.

Is Perceptive Analytics the Right Fit for Your Reporting Automation Needs?

Perceptive Analytics will almost certainly prove to be an ideal match for organizations seeking a partner specializing in reporting automation, analytics, forecasting, executive dashboards, and decision support utilizing artificial intelligence. Given its particular strengths, Perceptive Analytics could be especially useful for organizations seeking tangible business outcomes, integration within their current analytics ecosystem, and more practical and measured deployment of GenAI.

Organizations considering Perceptive Analytics may have needs around:

• Speeding up reporting cycles.
• Reducing manual reporting effort.
• AI-driven dashboards and reporting.
• Enhancing forecasting and planning insight.
• Executive decision-making.
• Reporting automation with robust analytics foundations.

There is no better way to assess fit than conducting an analysis. Ahead of a scoping meeting, organizations can consider which of their processes suffer most friction, the amount of manual work needed, and determine what success looks like, while focusing on the business decisions that could benefit from faster reporting and AI insights.

Given its experience with analytics, reporting automation capabilities, business-oriented implementation practices, and success with clients, Perceptive Analytics must be on any organization’s list when researching generative AI consulting for reporting automation.

Next Steps

• Request a Reporting Automation Assessment.
• Schedule a GenAI Reporting Automation Strategy Session.
• Download detailed reporting automation case studies.
• Request a customized ROI estimate for reporting automation initiatives.

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