How can IT be removed from Financial Reporting

How can IT be removed from Financial Reporting?

How can IT be removed from Financial Reporting

If you are asked to present up-to-the-minute information on cash flow, chances are you would create a worst-case scenario based on some new assumptions, such as a 20% decrease in sales and a 15-day delay in collections. Even though you’ve generated hundreds of cash flow reports, you’ve never been asked for this exact version before. It requires some additional details, such as a sales pipeline review and improvements to the aging study. Almost anyone who has ever worked in finance or accounting has encountered a situation like this at some stage. With the coronavirus outbreak, business leaders couldn’t bear to have inefficiencies slowing their access to the information as they tried to evaluate the situation and react quickly.

Eradicate the Chokepoints

To produce or change system reports, the finance and accounting department has mainly focused on IT experts or costly outside consultants. Many accounting and ERP frameworks provide report design tools that are inflexible and require a steep learning curve. This raises a variety of difficulties. For starters, it establishes a reliance on a third-party department. Cross-team dependencies are common in most organisations, but when one department’s goals vary from those of others, conflict or chokepoints occur, preventing work from being accomplished quickly and efficiently.

When a particular department is overburdened with conflicting interests, problems may occur. Many IT divisions were preoccupied with tasks related to the enablement of remote staff as the coronavirus crisis unfolded, for example. This occurred at precisely the moment when C-level executives required the most urgent access to financial data and analysis. Businesses can try to remove these forms of dependencies as much as possible as a long-term strategy, so those cross-functional collaboration strategies will concentrate on areas where teamwork and diverse viewpoints add real value.

Enhance Flexibility

The second issue with conventional reporting tools is that they often lack the versatility that finance and accounting users need. Because of its immense strength and versatility, most F&O users tend to work in Excel. Excel is an excellent tool for manipulating, analysing, and visualizing data. Almost every finance expert knows how to make good use of it. The finance and accounting department will kill two birds with one stone by allowing real-time data from various software systems to be accessed directly inside Excel.

For starters, they may reduce their reliance on technology. Second, they will enable finance and accounting professionals to create reports and conduct analyses using a single, strong, and familiar tool. Many businesses have found interest in implementing web-based dashboards so that leaders around the enterprise can have real-time access to a shared collection of business metrics. A few of these web-based dashboard platforms follow a common user-empowerment philosophy, allowing the finance department to set the agenda and implement a strategy for carrying out corporate dashboards without relying on the IT department in the long run.

Eliminate Errors

When finance takes over the reporting role, it will be able to address another issue that most F&O teams are familiar with. Traditionally, manually copying and pasting data from ERP, CRM, and other internal systems into Excel was needed for reporting and analysis. It is a time-consuming procedure that is prone to introducing errors into the reporting process. As data source formats alter (for example, when a new row is added to a General Ledger report), data may be pasted incorrectly into a pre-defined Excel template. Expert spreadsheet users will also incorporate error-checking algorithms or workarounds to avoid incorrect results in this case, but such methods are far from foolproof.

Another major disadvantage of the copy/paste process is that it is time-consuming. It generates reports that are based on out-of-date data. Data extracted from a source system, such as ERP, no longer provides an accurate and up-to-date picture of what’s happening in the industry. Data must be updated, and then copy/paste procedure must be repeated to review reports. Building a reporting strategy focused on real-time data access is a safer option.

An Alternative Approach

Take into account this alternative strategy, in which data is made accessible in real-time by connecting to multiple source networks within the enterprise. Because when the finance department can create reports directly in a familiar method like Excel instead of having to copy and paste data from other systems, it can concentrate on what it does best: compiling and evaluating data to make better business decisions.

The need to refresh content won’t arise since this system enables real-time access to information. Direct links to source systems such as ERP or CRM may be used to automatically refresh data. With less effort, less cross-team dependency, and a lower risk of mistakes, everybody gets a real-time view of what’s going on in the company.

All of these advantages are open to companies using several off-the-shelf ERP, CRM, and other software systems due to Global Data 365‘s powerful reporting tools. Reports can be created, updated, and distributed securely within the organization. Users only have access to information that they are allowed to see due to built-in data protection. The year 2021 will see a renewed emphasis on software automation tools. Automation of reporting and related tasks is a reasonable first step for companies looking to improve efficiencies by doing more with less, and remote workers aim to collaborate easily and efficiently with other team members.

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Why is Building a BI Strategy Important

Why is Building a BI Strategy Important?

Why is Building a BI Strategy Important

One of the many problems we hear from business executives is that they are still having trouble getting straightforward and reliable reporting from their business software systems. They recognize that they have a large amount of data, but the method of extracting, arranging, and evaluating it still seems to be much more difficult than it should be. That is why Global Data 365 was formed: to make the process easier, more efficient, and available to everyone in the company.

Business intelligence is the method of transforming raw data into actionable information. It helps you to gather data from various sources, arrange it, and then analyse it. In recent years, BI has exploded in popularity among small and mid-sized businesses (SMEs), owing to advances in technology that have made powerful analytics accessible to businesses of all sizes.

When you realize the real business advantages that powerful reporting can offer, BI resources provide a very good return on investment. A BI strategy will enable you to solve all of your data problems and requirements, create a coherent structure, and sustain it. What happens if you begin BI implementation without a plan? In other words, if you are focused on making those graphs, but no one in the business understands why or how to use them.

There is no one-size-fits-all solution because every other organization is unique. In the end, it’s all about figuring out where the company is now, where you want it to go in the future, and how you will get there.

Why Stock Reporting Tools Are Not Effective

Most businesses already use a variety of monitoring methods, and they may not even be aware of how disorganized their processes are. Consider the different tech platforms that your company employs. The majority of businesses use an ERP system to manage their financial and operational activities daily. Some companies have their own CRM system that may or may not be integrated with the ERP. Others use a digital marketing automation tool to generate and develop leads, improve customer interaction, and increase brand recognition and reputation.

These structures have their own set of reporting features. Unfortunately, such methods are frequently intended to be effective. They meet the basic reporting criteria, but they are limited in terms of versatility and complexity. Those tools, in many cases, lack the ability to generate custom reports. Frequently, current reports cannot be modified to benefit the organization’s strategic, complex business processes.

ERP software, in general, is infamous for requiring specialized IT skills for report creation and customization. This entails allocating limited IT resources to the task or hiring costly outside contractors to complete the task. Accounting, inventory, sales, and buying are the only areas where ERP reports can provide details. There are some consumer data there, but it is likely to be minimal.

To some degree, integration can help with the issue of information silos, but it can only go so far. However, some companies have begun to realize that time-consuming workarounds are inevitable disadvantages. The process of running reports through two to three different systems, then exporting the information to Excel, and forming a report takes time and manual errors.

BI systems must address the differences between all of the software systems that business leaders rely on to control their businesses to deliver genuinely accurate reporting that offers a unified view of the business. A successful BI platform should deliver data in real-time and be simple enough to use that everyone in the company can create and change reports without needing specialized skills.

Cloud ERP

As companies move toward cloud ERP, they must think about the consequences of reporting and analytics. Most tech providers have taken the requisite measures to change the way you access data as they have moved to a cloud-first approach. Businesses that used a cloud ERP framework will no longer render direct database queries using structured query language due to security concerns. This is a technological transition, but it has far-reaching consequences for business intelligence.

As companies move to Microsoft Dynamics 365 Finance & Supply Chain Management from Microsoft Dynamics AX, for example, they will have a variety of options for accessing data and running reports. A better solution for businesses looking for a dependable BI platform with a low total cost of ownership is to look for a robust, validated reporting and analytics product that is optimized for high performance and ease of use.

Powerful BI Strategy

In any company, BI can be used to effectively improve operations.  Everyone will concentrate on the same goals, collaborating with the same KPIs to push action and develop procedures, when the whole team is working from the same strategy and has access to a common source of reality. Although technology is a part of every discussion about business intelligence, it should not be the baseline. An effective BI strategy must address the requirements of the organization’s financial and operational decision-makers. It should meet financial and operational reporting needs with powerful and adaptable tools that enable everyone in the company to create and adjust ad hoc reports without requiring advanced training or IT skills.

At Global Data 365, we provide effective business intelligence solutions to meet your company’s needs. Some major questions that make their BI strategy effective are:

  • What are the record systems of your business data?
    These are typically the starting point for creating a cohesive approach to reporting, putting together data that provides business leaders with a comprehensive picture, a unified understanding of what’s going on in the company.

  • In the company, how does your team use reporting?
    Which reports do decision-makers consult on a regular, weekly, or monthly basis? What happens if you need an urgent report?

  • Are the financial reporting systems capable of completing period-end closing quickly and efficiently?
    Is there a way to make the period-end process more efficient and automated? Do the numbers in the general ledger and sub-ledgers of the ERP method immediately connect to the reconciliations and supporting worksheets?

  • When do the stakeholders receive the information?
    Have you ever had a situation where you wanted details right away but couldn’t get it? What were the consequences of the delay?

  • Is your company thinking of shifting to cloud ERP or cloud CRM system?
    If it is so, you must link with a provider who can meet your needs both now and in the future when you migrate to the cloud.

When you answer these questions, it can help you figure out what you want to do with BI in the coming years, as well as the kinds of benefits your company will reap in the short and long run.

At Global Data 365, we satisfy the requirements of the finance and accounting departments. Usually, when companies are implementing a BI plan, the finance department’s specific reporting requirements are ignored, but with Global Data 365 onboard that won’t happen, as we prioritize customer satisfaction.

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Where BI fits into your Data Strategy

Where BI fits into your Data Strategy

Where BI fits into your Data Strategy

Traditional data techniques have been based on business intelligence (BI), but the advent of predictive and prescriptive analytics platforms, due in part to machine learning and artificial intelligence, is shaking things up. Also, business intelligence is changing, with features that were traditionally only available on business analytics platforms. Analysts and consultants believe that knowing the differences between business intelligence and other analytics tools and the value each brings to the organization is critical to developing an effective data strategy.

Here, we will look at where business intelligence fits into the current analytics landscape and how business analytics is changing as tools, strategies, and staff requirements change.

Business Intelligence vs. Business Analytics: What’s the difference?

In the widest sense, analytics refers to any technology-enabled problem-solving activity. Experts classify analytics into four groups on a scale of one to four, with descriptive and diagnostic analytics on the lower end of the scale and predictive and prescriptive analytics on the higher end. When starting an analytics system, most companies start with BI, which is part of the descriptive process. Business intelligence is the method of transforming data into actionable intelligence that helps an organization make strategic and tactical decisions. It’s what makes it possible for a company to collect, analyse, and present data.

It’s all about the data, according to Beverly Wright, executive director of Georgia Tech’s Scheller College of Business’s Business Analytics Centre. It isn’t attempting to do something other than telling a story about what the data is showing us. While some business people can associate BI with analytics, Wright says data professionals differentiate between the two. Some define BI as providing insight into what has occurred, while others describe analytics, especially advanced analytics, as predicting what will occur in various future scenarios.

Business Intelligence for Business Use

BI uses more organized data from conventional business platforms, such as enterprise resource planning (ERP) or financial software systems, to provide views into previous financial transactions or other past activities in areas like operations and supply chain management. According to analysts, BI’s importance to companies today stems from its ability to provide insight into such areas and business tasks as legal reconciliation.

According to Wright, BI tools, like many other parts of the business technology stack have developed to become much more intuitive and user-friendly. She describes that in the past, companies used data scientists to use these systems to create dashboards. They’re now completely automated. As a result, companies can more effectively implement data systems that enable non-technical business owners to use BI tools to generate reports and obtain much of the information they need without involving data professionals in day-to-day operations. Analysts believe that this alone qualifies BI technologies as critical business tools.

BI as a Gateway to Business Analytics

While reporting solutions and other BI tools have a position in the enterprise, analysts claim they have limited capabilities. Bain & Co., a multinational management consulting company, estimates that more than half of companies use at least three separate analytics providers to produce performance reports in its 2017 study Six IT Design Rules for Digital Transformation.

BI tools don’t offer the kind of in-depth data analysis that can lead to new market opportunities and development. According to John Myers, a senior analyst in business intelligence, “BI is not driving sales and innovation.” Enterprise Management Associates employs intelligence. Even though Myers reports that 20% of US businesses are already at the BI level, he believes that most companies do not want to stop using analytics, and attempts are being made there. Users can begin by looking at sales data and then want that data is calculated by state or product, according to Myers. Then they’ll like to see their top 10 customers from the previous year, as well as their common characteristics, and forecast which customers will be in the top 10 in the coming year based on that detail.

BI as the Future

While data professionals continue to play important roles in advanced analytics, such as modeling, Myers says their participation varies depending on the business case. To detect possible credit card fraud, for instance, advanced analytics systems rely on unmonitored models rather than data scientists querying the systems. Organizations generally buy off-the-shelf BI products as well as commercial advanced analytics products, Myers adds, but they tend to have their own data professionals build the machine learning and AI capabilities they need because there’s not a set of packages on the market; the products just aren’t there.

Many BI tools, according to Brahm, are bringing in more and better data signals to generate more reliable, informative reports that blur the boundaries between BI and more advanced analytics. He believes that these new technologies are assisting users in making better decisions by answering questions about how to maximize and optimize the business, such as who the company can target, what promotions are available, and which ones are available to whom.

Technology organizations are more advanced in their implementation of advanced analytics capabilities, such as machine learning and AI, and are more likely to have done so already. If you find more about how BI is helping to transform businesses, contact us.

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The Future of AI in the Business World

The Future of AI in the Business World

The Future of AI in the Business World

When it comes to the implementation of Artificial Intelligence (AI) in an enterprise, the world is at a crossroads. Although the technology that allows computers to mimic human thinking has advanced steadily over the last half-century, the cost-effectiveness of deployment, convenient access to cloud computing, and realistic business use cases are all positioned to help AI make a major impact in the business world in the coming years.

With the future use cases for AI in the industry on the way, and also the capital investments and speed of progress currently powering AI, one thing is for sure: To realize the benefits flowing to the business world, you’ll have to get your framework in place relatively soon. But how are you going to do it? Business intelligence (BI) tools can help with this. Businesses can plan for the future while still taking full advantage today by laying the groundwork with this readily available, open, and inexpensive software. Businesses are starting to question if it makes sense to move through an expensive deployment that won’t produce meaningful results for two or three years after having unrealistic expectations for AI, which have yet to emerge. Instead, they should concentrate on implementing BI today to get some quick results, then layering AI on top of existing BI data to extract new insights and generate greater value as the technology advances.

So, how can BI apps assist in preparing the company for AI, and what potential use cases can be derived from the combination of AI and BI?

What can BI Software Do for You?

Whichever side of the Artificial Intelligence and Business Intelligence discussion you are on, one aspect is certain: you’ll need data to support both. There is no intelligence in AI or BI without data to operate on. There will be nothing to analyse or to which a learning algorithm can be applied. When it comes to intelligence solutions, data is the cornerstone that must be laid.

Data has never been more accessible in today’s business world due to the wider acceptance of cloud computing and the Internet of Things. However, the massive amounts of data produced every day are posing a new challenge for businesses: What knowledge is crucial? What are the best practices for tagging, sorting, grouping, and analysing data? What concerns are answered by disparate data points? How can data collection through various touch points, from retail to supply chain to a factory, be seamlessly implemented?

Data Warehouse

This is where data warehousing comes in. Data warehouses are a way of optimizing data obtained from various touch points, like point-of-sale, CRM, inventory, and warehouse management systems), structuring it to obtain needed insights, and running research. Enterprise companies cannot thrive without efficient data warehousing; data silos consume capital and resources quickly, and any company still attempting to piece together “business intelligence” from numerous reports and fragmented data will quickly fall behind those with centralized data and reporting. The integrated data warehouse, on the other hand, isn’t just a set of relational databases thrown together; it’s based on modern data storage systems like Online Analytical Processing (or OLAP) cubes.

Cubes are multi-dimensional data sets designed for analytical processing applications like AI or BI. Cubes are superior to tables in that they can connect and sort data across several dimensions, enabling non-technical users to access a wider wide range of role-specific and highly contextual data points to discover new insights and make real-time adjustments to strategies and decisions. Most non-technical sales agents and buying associates will struggle to link several tables along with a standard report, but with Business Intelligence cubes, all they have to do is drag and drop the metrics and dimensions that apply to their own customized dashboard.

So, how do you get the data? SQL is a language for manipulating and extracting data from cubes. SQL was created as a common language for interacting with databases, irrespective of the type of database being used, and is ultimately the tool for extracting, retrieving, deleting, modifying, and handling data in a table.

Other Methods to Address Data Demands

Aside from data warehousing and OLAP cubes that provide the technological base, there are a few other components that can assist enterprise businesses in meeting their data needs:

Data Modelling

Data modelling is a technique for sorting out individual data sources within an organization and deciding how they should communicate to obtain the most useful business insights. Data Modelling can be done at the conceptual (high-level, linked to business objectives), logical (mapping to each business function), and physical (how the actual measurements, metrics, and structures are related inside a data cube).

Analytics and Reporting

The ability to capture, structure and store data is essential, but the ability to analyse and report on it is the ultimate objective. End users can find the valuable insights they need with little technological expertise due to business intelligence solutions that provide easy, open analytics and reporting functions. It also facilitates business processes in avoiding unnecessary data bottlenecks by providing them with immediate access to the data they need.

Data Visualization and Dashboards

Business intelligence relies heavily on analytics and reports, but you are not alone if you have ever spent hours sifting through a table of values trying to find out what the data means. Important insights are presented in vivid graphical representations that are much easier for the user to understand using data visualization tools. According to Aberdeen Group research, businesses that use data visualization software are 28 percent more likely to find accurate information than those that depend entirely on controlled reporting; the same research also found that 48 percent of business intelligence users at companies with visual data exploration will find the information they need without the assistance of IT personnel. Dashboards can quickly compile visualizations and reports into customized displays for each end-user or business activities, by providing individuals with immediate access to KPIs that help drive improved business results from the ground up.

Protection, usability, and efficiency are three major benefits that business intelligence solutions help to drive, as well as three key indicators of enterprise business performance. Protection, usability, and efficiency are three major benefits that business intelligence solutions help to drive, as well as three key indicators of enterprise business success.

The Future of AI

Soon, AI algorithms will be expected to be efficiently implemented in your current data stores, providing you with even more insight. AI applications in line with business should fall into three categories:

Automated Processes

The most common use of AI in the business right now is to automate systems and business processes. Although previous iterations of automation focused on sharing data between systems, AI can take this skill to the next level by interacting with data as if it were a person, either inputting or consuming as required. AI robots are now capable of analysing legal contracts and extracting specific clauses, updating customer records through several networks, and automating customer outreach in response to changing circumstances. Businesses will be able to automate even more processes as these algorithms become smarter.

Meaningful Insight

Cognitive insight is the ability to derive meaning and distinguish patterns from large amounts of data using AI algorithms. Although BI software and data stores will certainly include the “diet” for cognitive insight algorithms, as they learn, they will be ready to access those learnings to larger data sets, respond to new data in real-time, and recognize possible data matches across multiple platforms.

Cognitive Engagement

The human-interfacing aspect of AI is referred to as cognitive interaction. Consider chat-bots, knowledge bases, and product recommendation engines, among other things. Externally (for customers) or internally (for employees), cognitive engagement technologies can be used to simplify the connection between users and systems. Since companies are still wary of the relatively new technologies, most existing applications concentrate mainly on internal engagement. However, as AI growth and implementations progress, objections are likely to fade away as companies discover new ways to use existing data to drive practical automated interactions with humans all over the world.


In the future, artificial intelligence will eventually start to live up to its potential. We have been reading a lot about the excitement in the business world. Computers can assist in ushering in a new age. For cutting-edge businesses, a new age of growth and profitability awaits, but only if you have already laid the groundwork, which begins with business intelligence.

At Global Data 365, we understand that business intelligence and data management are essential components of every enterprise artificial intelligence strategy. To get the most out of artificial intelligence, you need to start with good reporting and analytics. So make sure you are laying the groundwork for your company’s future success today!

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Overcome Your Fear of Advanced Analytics

Overcome Your Fear of Advanced Analytics

Overcome Your Fear of Advanced Analytics

We have all read that information is nothing unless it can be turned into meaningful data. It can be daunting in business to have access to so much data. How do you know where to begin when you’re bombarded with information It’s possible to get lost in the midst of it all, overwhelmed by the flood of data and uncertain where to start looking for ways to improve business processes. That is where you can utilize advanced analytics.

Advanced analytics is the automated or semi-autonomous analysis of data using materials and tools that go beyond traditional business intelligence (BI). It’s a catch-all word for a number of analytics sub-fields that collaborate using predictive capabilities. High-level approaches and software forecast future patterns, activities, and events, allowing businesses to create “what-if” models and estimates to future-proof their operations.

Advanced analytics involves data mining, big data, and predictive data analytics, which allows you to mine your data for deeper, more analytical, and eventually actionable insights. Whereas traditional analytical methods show you where you’ve been, advanced analytics focuses on where you’re going next, providing insight into what could happen based on a variety of potential opportunity scenarios.

Advanced analytics includes newer technology such as machine learning and artificial intelligence, as well as visualizations. In reality, advanced analytics encompasses so many areas and has such a wide range of applications that it has a variety of applications, including marketing, inventory and warehousing, and manufacturing. Keeping this in mind, it appears that any company should be interested in using advanced analytics to solve critical business problems.

Assumptions Regarding Advanced Analytics

Many CFOs still have assumptions about advanced analytics:

  • They cost money.
  • They take time to deploy.
  • They are complex to understand.

Advanced Analytics is Costly

You might be wasting money if you’re sitting on a heap of useful data and aren’t analysing it because you’re afraid of investing in advanced analytic tools. Your data is your most valuable resource for uncovering answers to your potential questions by properly processing your history.

Many enterprise resource planning (ERP) systems quickly integrate with external services that are both dependable and cost-effective. When you are likely to afford less time doing the hard work and more time understanding the report findings, the rewards can quickly outweigh the costs.

Deployment takes Time

Yes, some technology takes a long time to get up and running. Running out the first ERP or switching to a new one is a lengthy process that can take months to complete, and that’s assuming everything goes smoothly.

This is not the case for advanced analytics. Many of these systems can be set up in a matter of hours, if not minutes, and begin crunching the data right away.

Complex to Understand

Although advanced analytics was developed to use complex formulas and equations, they are used to provide the end-user with data that is simple to understand. In reality, several advanced analytics user interfaces are built to help people from all walks of life use data to search for information.

Enterprise solutions can also assist users in learning techniques by assisting them in selecting and processing appropriate data from a variety of sources. The end-user’s experience will be simple to navigate, regardless of the technicality of what advanced analytics might be doing in the context.

Still Having Doubts?

If you’re still having doubts about using advanced analytics even after clearing out the assumptions, we are here to clear them out.

Begin by gathering the information you’ll need to examine. For your business, this may have been a time-consuming process in the past. Data is stored in an ERP (or two) as well as other diverse relational databases that don’t always get along. As a result, putting together the data could have required many data backups and several hours of manipulation to get it into the format you need. If the data changes during this phase, for example, if you receive a late invoice payment that still counts against the month you’re working on, you’ll have to restart the whole process.

Using Global Data 365’s finest reporting systems, you can connect data from more than 140 ERPs and EPMs, as well as other relational databases, into one automatic report that lives inside the framework of Excel or displays in a readily available web-based dashboard. Dynamic links are used in our solutions to extract real-time data from your ERP, connect it to other sets of data, and deliver the accurate reports you require based on safe and simple-to-assemble parameters.

With one click, you can check your reports. Return information for a single account, a collection, or a wildcard quest. It’s all designed to offer users quick and easy access to their data so they can spend less time figuring out what is going on and more time predicting the future.

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9 Ways you are failing at Business Intelligence

9 Ways you are failing at Business Intelligence

9 Ways you are failing at Business Intelligence

Business intelligence is critical for making strategic business decisions, but often organizations’ BI efforts are hindered by bad data practices, tactical errors, and other factors. Executives understand the importance of having high-quality data when making business decisions. However, obtaining reliable data in a timely and user-friendly format continues to be difficult. Yes, there is a thriving market of business intelligence (BI) analysts and distributors.

How can you determine if your business intelligence (BI) is failing and it’s time to update or recruit specialist experts? Knowing where others have gone wrong will help you answer these questions.

Doing What Customers Ask, Instead of What a Company Needs

Surely placing customer satisfaction as the top priority leads a company to success. However, when it comes to technology, business users can not always grasp what they are requesting. Apart from that, they try to impose the solution’s technical information.

BI failure is a result of implementing what consumers want rather than what they need. Successful BI projects necessitate the ability to adequately verify BI findings, and the ability to elaborate and manage requirements. One way of understanding what consumers really need is to use the “five whys” approach, which involves asking why five times about a single problem to gain greater depth.

Using Less Time and Money for Testing

In the marketing world, think about moving fast and break things is a common mantra. And well-established companies need pace. However, in the race to go faster, things that are seen as additional services, such as testing, will suffer. Seeing testing as a waste of time may lead to serious quality problems, particularly if manual testing is used. Instead, look to research and related “ancillary” processes to provide a better BI experience.

Limiting testing, particularly when the only testing performed is manual, results in a higher number of errors in user testing, which has an impact on product delivery.

Short-Term Broader Data Integrity is Important

Reading, viewing, and analysing data is a convenience with business intelligence software. But what if the data you’re providing the system is tainted? Or, to put it this way, how can you show an IT analyst that your management decisions are based on high-quality data? If you concentrate solely on the BI tool and its setup, you can overlook this crucial information.

Taking a Defensive Approach to Unsatisfied Customers

Dealing with irritated users is not something any technology expert looks forward to. There will be system errors and annoyance points. Your response to these issues will determine whether or not your BI project succeeds.

The two most common mistakes that BI new comers make are concentrating all their attention on delivering requests and failing to include business end-users in the project. What matters is, are you providing your customers with the information they require to make decisions? Do you know what information they require? Is there an alternative to making a new report to solve the problem? It’s preferable to prioritize user complaints based on their relative relevance to your overall plan rather than simply dismissing them.

Conducting Analysis With No Purpose

When you have effective resources at your side, it’s only normal to look for ways to use them. Business intelligence without guidance, on the other hand, is a waste of time. This issue is especially prevalent among young professionals.

Inexperienced and eager business intelligence practitioners risk developing tunnel vision and doing interesting research that isn’t motivated by meaningful questions. The findings often lack a ‘so what’ finding and struggle to offer actionable insights. It takes business knowledge and judgement to avoid this blunder. One way to avoid the “so what” dilemma is to ask yourself, “How does this research apply to the company’s goals?”

Thinking Data is Sufficient

Is it possible that “more data” can solve all of our business problems? Many aspects of business intelligence and analytics are based on this unspoken presumption. It’s not going to be working to just drop data at an executive and hope for the best.

Data is dismissed or trumped by belief if it isn’t interpreted and argued convincingly. The importance of making a strong case and crafting a compelling narrative can never be underestimated. The field analysts may be aware of the implications of data collection. You can’t presume that those who are a few steps away from the data will understand that argument.

Relying only on BI tools

Technologists understand that the right method will make a huge difference. Consider the first time you used a script to automate a time-consuming process. Those early victories motivate you to keep looking for new ways to solve business problems. Unfortunately, putting too much reliance on your business intelligence tool can lead to disappointing results.

Even if the tools are becoming more user-friendly, there are process, cultural, and learning elements that must be addressed to achieve progress.

Vendor Management is Ineffective

It is possible that your organization doesn’t have a business intelligence department. Working with outside experts makes sense in that situation. You could hire them to act as an outsourced service provider or to help on a particular project. In any case, you must know your vendor and provide oversight, particularly when it comes to subcontractors.

It is your duty to manage the problem and figure out who is working on your behalf if a third party is involved. Otherwise, you might be in for a BI failure.

Dismissing Tools like SQL and Excel

Are you aware that there are Microsoft Excel championships held every year? Take, for example, the Microsoft Office Specialist World Championship, which attracts over 500 thousand participants and offers cash prizes to the winners. That is just one indication of Excel’s growing popularity in the corporate world. SQL has a large following in the technology community but to a lesser extent.

Therefore, making a big shift to BI in a company has ramifications for employees’ jobs. In leading people through the process, the practice of change management and leadership cannot be overlooked.

If you’re interested in knowing how agile BI solutions can lead your company to success, contact us now.

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Power BI with Jet Analytics

Power BI with Jet Analytics

Business intelligence is a much better and less expensive choice than data warehousing for 90% of small to mid-size businesses. Both of these systems have the same overall goal in mind: to improve data analysis. The immense effort and cost needed to define the data tables and relationships required to drive analytics put data warehousing out of reach for most businesses. Due to the extreme minimal effort and expense needed to get it up and running, business intelligence is becoming the choice of small to mid-size companies, irrespective of which of the two most popular options are used.

Jet Analytics from Insightsoftware (previously Jet Global) and Power BI from Microsoft are the two most popular business intelligence options in the Microsoft Dynamics environment. Jet Analytics can use either Excel or Jet Reports as a reporting tool, allowing you to have the best experience. Jet Analytics uses pre-defined data cubes to describe the patterns in the data necessary for reporting. Because the table relationships required for accounting, which are focused on financial processes, are not always the same as those required for business analysis, which could be more operational, this method works. This method has many disadvantages, including a higher initial cost, more work to create new data relationships into the data cubes, and the fact that data is only as current as of the last update. A major benefit is a simplicity with which new reports can be created if they match the data cubes, as well as the improved accuracy since the reports are run against a replica of the output database rather than the live database itself. Data can be processed into data cubes from a variety of sources, not all of which are accounting systems.

Benefits of Power BI

Power BI depends on one or more databases to provide real-time or near-real-time data. This means that data is updated in real-time, but output for more detailed reports will not be optimal. Almost any form of the report can be created and distributed through the web or mobile devices. Every consumer can create their own dashboards, each with its own unique insight. It is possible to set up alerts. The details behind the reports can be drilled down by users. To use Power BI, you will need an Office 365 subscription.

Find out more about what is Power BI
Learn the limitations of Power BI and how to avoid them

You cannot really go wrong anyway. Invest a little more upfront to identify data relationships using data cubes in Jet Analytics, or subscribe to Office 365 and use Power BI to provide your users real-time access to important analytical data. To explore more about these better, less expensive alternatives for your company, we offer 30 days free trial license for you to test it on your very own database.

Contact one of our BI expert and schedule a personalize demo now.

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Optimize Processes with Data Visualization

Optimize Processes with Data Visualization

Optimize Processes with Data Visualization

Every aspect of a company relies on making prompt, well-informed decisions. Data is at the center of the financial services sector. Traditional business intelligence (BI) methods aren’t up to the task with so much data to rummage through. These techniques were designed for tabular reporting and can only handle small volumes of homogeneous data; they also require advanced technical expertise. Today’s software can process and interpret massive amounts of data in real-time, with a level of elegance previously unseen. According to a report conducted by Gartner on the top priorities of CFOs, here’s what they looked at:

  • Enhancing Financial Analytics: Even after a 50% rise in financial analytics expenditure in the last three years, only a few businesses have advanced analytics capabilities. As analytics becomes a central responsibility of the finance department, this must change.
  • Reorganizing Finance Teams: Traditional approaches for coordinating and using finance teams are becoming less effective as the popularity of finance teams grows. To stay relevant, the department needs a shakeup from the top down.
  • Finance Technology Optimization: Finance teams must maximize the value of their ERP systems while also adopting newer innovations and planning to become more tech-savvy. If this isn’t done, the finance department will become less intelligent and agile.

Any of those projects could keep a CFO busy for a year without yielding much progress. However, if such executives consider these problems analytically, realizing how the challenges and goals intersect, a surprising approach emerges, data visualization.

Data Visualizations

There has almost certainly been some kind of data visualization for as long as there has been data. Charts and graphs have recently become commonplace in business due to Excel spreadsheets. Users soon realized that visual interfaces help them understand complex information. Instead of manually examining a spreadsheet, they could quickly recognize the key takeaways by looking at a pie chart. Digital visualizations provided the finance team with a completely unique outlook on data and a game-changing method for decision-making, compared to what had previously been available.

Today, visualizations have taken yet another step forward, possibly the most important yet. Advanced visualization features are included in today’s top financial reporting tools, which run on top of ERP and beyond the constraints of Excel. Such visualization tools do more than improve on what has come before; they turn the relationship between the finance team and the data on which it relies more highly than it has ever been.

Advances in Data Visualizations

So, what’s the difference? To begin with, visualizations have progressed well beyond basic graphs and maps. They can now visualize data in new systems that provide more context and information. Users can view the optimal visualization to encompass the data rather than trying to settle for a sufficient option with this enlarged toolkit at their disposal.

After you have made that decision, creating the visualization is nearly seamless. It only takes some clicks to move data from one area to another in several cases, rather than a lengthy manual process. This not only saves time and eliminates mistakes, but it also helps everyone inside or outside the finance department to create their own visualization without any need for advanced training. Lastly, and perhaps most critically, visualizations have moved to the foreground of decision-making. The finance members can quickly integrate them into financial reports and structure them to optimize the insights they contain as well as the ease with which they can be extracted. The design features within such reports are also not static. They update themselves as new information becomes available, making them more like interactive indicators that monitor key metrics in real-time than visualizations.

Everything in today’s visualizations is vastly superior to previous versions. Despite this, it’s always easy to underestimate their effect on the economy. The CFO, the finance team, and the company as a whole are all involved.

Using Data Visualizations to Optimize Processes

Data visualizations not only help people view data in new ways, but they also help them see it more clearly, presenting insights, opportunities, and challenges that would otherwise go unnoticed.

One form of data visualizations does this is by compressing large volumes of data into some kind of layout that is readily available. Financial reports influence decision-making, but in the past, they were either too simple to show anything of value or too difficult to stir up an action. Today’s visualizations bridge the gap, allowing reports to include what decision-makers need to know while still revealing those insights in real-time.

Advanced data visualizations also allow F&a to investigate financial data on their own terms. Decision-makers know what knowledge they want better than everyone else, and once it’s simple to find it and visualize it as needed, understanding differences disappear. To look at it another way, visualizations open up a vast array of nuanced financial data to the point that it can be explored. Anyone interested in delving deeper into the data now has a great starting point.

Visualizations help practitioners outside finance grasp a topic that can be perplexing to the general reader, in addition to CFOs. Executives and heads of departments need to consider how their decisions impact the company’s finances on a micro and macro level, but many lack the knowledge to do so of a dense spreadsheet presenting a financial report. However, when presented with visualizations, the material emerges in a manner that everyone can comprehend. As a result, financial knowledge grows around the board.

Why Power BI is a better choice than Excel
Why is Good Data Management Essential for Data Analytics

Data Visualizations: a Modern Solution

Finance teams will use innovative data visualizations to make significant progress on every one of 2021’s top priorities. Once implemented, analytics improve dramatically, accountants spend less time manually processing data, and the ERP ceases to be a barrier to understanding.

Global Data 365 offers visualization tools to optimize finance processes. In terms of usability, precision, and variety, these resources far exceed what you’ve come to expect from Excel. Even better, they’re just one of many features available in purpose-built financial reporting tools that are designed to work with today’s most common ERPs.

If you’re searching for a new perspective on data, we offer a comprehensive upgrade. To see how this all operates, request a free demo today.

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Cash Flow Analysis with Microsoft BI

Cash Flow Analysis with Microsoft BI

Cash Flow Analysis with Microsoft BI

With the advancement in technology, it is more important than ever to understand how cash flow affects your company and how technology, such as business intelligence (BI), can help you keep track of your cash.

What is Cash Flow Analysis?

Financial reporting requires the use of cash flow analysis. You can tell where cash is produced and invested by looking at your company’s cash inflows and outflows over time so you can prepare accordingly. Controlling your cash will help your company not only stay afloat through difficult times but also open gates to new opportunities.

Have you had a profit or a loss? Cash flow is important at any point of a company’s development cycle, whether you’re a new start-up or an existing company. Anything you do requires money, from managing assets to hiring a new employee. To achieve security and consistency, you must have the right tools and structures in place at the right time to help you manage and predict your cash flow.

Different Approaches to Cash Flow Analysis

At the end of each quarter, most accounting teams are responsible for conducting a cash flow analysis to determine that all of the company’s expenses are taken into account.

Free Cash Flow (FCF) is among the most valuable financial performance indicators. Experts look at FCF or operating cash flow minus capital expenditures to determine how much money a business has left over to broaden or return to shareholders. You have an issue if your expenditure exceeds your income.

A cash flow statement is a crucial tool for managing cash flow, and it contains data from operations, investing, and financing. A cash flow statement is traditionally created to use Excel-based manual data analysis. It can be difficult to combine data from your cash flow analysis, expected and real operating expenses, capital expenditures, accounts receivable/payable balances, and general ledger data. Excel costs time and money. Identifying the ramifications, many businesses have simplified manual accounting processes and adopted business management and intelligence technologies to better analyse and predict cash flow.

Learn Difference Between Financial Reporting and Management Reporting

Cash Flow Analysis with BI

Companies have embraced business intelligence technology to change the way they handle their cash flow now that the platform is more available and affordable. Companies use business intelligence and analytics software to automate cash flow analysis and provide the tools they need to analyse data optimize cash flow analysis, and more.

The best feature of business intelligence software is that it is designed to provide more precise financial statistics and, as a result, eliminate the guesswork from the cash flow analysis process. BI solutions provide managers with reports that are timely, reliable, and simple to use.

Here are a few examples of how BI is assisting companies all over the world in better managing their cash inflows and outflows.

Intelligent Predictions

Financial predictions enable you to prepare for the allocation of resources and budgeting by providing a clear way to making strategic business decisions. Cash predictions can be generated automatically using BI software. Financial managers can remain updated at all times with this ability, including advanced warnings of cash shortages or surpluses. This enables a business to respond rapidly to growth potential or to cut back when necessary.

Data Management

Assembling data from various sources is the most time-consuming aspect of cash flow analysis by spreadsheet. You will get the figures you require in real-time using BI software that combines with your ERP and CRM solution. The cash flow analysis will provide more useful insights and up-to-date reports, allowing you to make fast, data-driven decisions.

Manage Projects

Large projects may have a significant impact on cash flow. For cash flow development and proper development, financial managers need greater control of what goes in and what comes out, so the ability to analyse a project’s length, expenses, resources needed, and payment terms is critical.

Plan Inventory

There are some costs involved with the inventory. It not only binds up cash in goods but getting too much inventory can also be harmful to your cash flow. You will make a decent source of supply and be more careful with inventory spending with BI tools. In the long run, BI will save you a lot of time and money by sales forecasting and intelligent reporting.

Risk Management

Should you put money into a new venture? Should you temporarily reduce your spending? Risk management software such as BI software is a reliable tool. If you have a cash flow problem, if your prediction indicates that you may not have enough cash, a BI solution will enable you to perform a fast prediction and liquidity analysis to assist you in making the best decision possible.

BI Solution

BI tools help data-driven analysis and decision-making, which is just what you need to keep a tight grip on your cash flow. Although there are many BI solutions available today, particularly for Microsoft Dynamics users, there is no such thing as a “one-size-fits-all” solution.

Learn More About Why BI Implementation Can Be Risky

We are here to assist you if you want to improve your financial statements and cash flow review. Contact us today!

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How Does Business Intelligence Help in Demand Forecasting

How Does Business Intelligence Help in Demand Forecasting?

How Does Business Intelligence Help in Demand Forecasting

Businesses are investing significantly in advanced analytics to maintain a competitive advantage and improve their result due to big developments in artificial intelligence and machine learning. Predictive analytics is one of these fields in which businesses extract information from existing data to assess purchasing patterns and predict future trends.

Predictive analytics makes use of a combination of data, statistical algorithms, and machine learning approaches to predict the likelihood of future outcomes based on the past. Every sector, from banking to retail, uses this technology to assess consumer responses or orders, forecast inventory, manage capital, and even detect fraud. Predictive analytics is becoming more popular, even though it has been around for decades, thanks to increasing quantities of data and readily available tools ready for a transformation.

Increase Revenue with Financial Reporting tools

Below we will look at how market intelligence can help with demand forecasting, a type of predictive analytics that focuses on consumer demand. We’ll go into what demand forecasting is, how it operates, and how to get started with it using business intelligence tools.

What is Demand Forecasting?

Demand forecasting is a type of predictive analytics that focuses on predicting customer demand for products and services. It estimates potential demand based on historical data and current market conditions and sets the level of supply-side preparedness needed to match demand.

Demand forecasting is important in production planning and supply chain management, even if it isn’t an acquired skill. Demand forecasting impacts everything from budgeting and financial planning to capacity planning, sales and marketing planning, and capital investment.

Why Should You Use Demand Forecasting?

Manufacturers, distributors, and retailers use demand forecasting as an important part of supply chain planning to gain insight into their activities and make educated, efficient decisions about pricing, inventory stock, resource optimization, and more.

Listed below are some major reasons why demand forecasting is so important in today’s supply chain:

  • Increased customer loyalty (providing customers with the items they want, whenever they want it).
  • Inventory management to minimize stock-outs and overstocking.
  • Effective raw material and labor scheduling.
  • Improved capacity planning and resource allocation.
  • Better distribution planning and logistics.
  • Affordable pricing and promotion.

Use of Business Intelligence in Demand Forecasting

Data is used in demand forecasting. If the data you use is incorrect, the math and how you apply it will result in under or overestimated demand, leaving you with a slew of disgruntled customers or an overabundance of goods. Most businesses use a business intelligence solution to help with data planning, data co-ordination, and forecasting to better understand demand and supply.

Business Intelligence with Power BI

Business intelligence software is designed to capture, unify, sort, tag, analyse, and report on large volumes of data. Here are four main areas where market intelligence can help you get started with reliable demand forecasting:

Data Preparation

Most businesses fail to cleanse, verify, and audit their data regularly. As a result, 40% of company data is either incorrect, incomplete, or inaccessible (Gartner). BI software allows you to organize and monitor your data in one place, ensuring that your analytics are based on reliable data.

Data Collection

A data warehouse can assist you in gathering business data from a variety of sources and using it for accurate reporting and analytics. Data warehouse-powered BI will help correlate data from different systems to provide further visibility into the supply chain, revenues, and financials, among other items.

Data Analysis

BI software is built for processing and measuring large quantities of data. Maintaining a system of records, which includes historical records and various data sources, ensures that all findings are based on the same version of the facts.

Reporting and Analytics

With pre-built dashboards, BI software will give you a single view of results and reports for the rapid dissemination and exchange of real-time information on demand. This encourages better preparation and coordination between the teams.

Improve your data quality and plan your data for reliable demand forecasting by learning more about what you need to do. At Global Data 365, we will analyse your current systems and show you how business intelligence will help you build the technology base for your company.

Contact our team for more information!

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