business intelligence

Where BI fits into your Data Strategy

Where BI fits into your Data Strategy?

Where BI fits into your Data Strategy

With the rise of predictive and prescriptive analytics, driven by advancements in machine learning and AI, traditional business intelligence (BI) techniques are evolving. BI is no longer just about historical data insights; it now incorporates features once exclusive to advanced analytics platforms. As organizations build out their data strategies, it’s crucial to understand the distinct roles BI and other analytics tools play. Knowing where BI fits into your data strategy is key to maximizing the value each platform brings and ensuring data-driven decisions are made effectively. 

 

Here, we will look at where business intelligence fits into the current analytics landscape. We will see 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 or 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. A good BI strategy, it’s what makes it possible for a company to collect, analyze, 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. 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 employ 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 to be 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. Forecast which customers will be in the top 10 in the coming year based on that detail. 

BI in Your Data Strategy

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 out more about how BI is helping to transform businesses, and where BI fits into your data strategy?  Contact us.  

How Global Data 365 can help you?

As a premier provider of Power BI services in the Middle East and Africa, Global Data 365 empowers organizations to streamline data management, gain actionable insights, and make smarter business decisions. Our expert team specializes in delivering tailored solutions that address the unique needs of each client, ensuring that Power BI maximizes impact across their operations. By understanding where BI fits into your data strategy, we help you leverage the full potential of business intelligence to drive growth and success. Trust Global Data 365 to elevate your BI capabilities and deliver measurable results.

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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 during 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 several 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, and visualizations. 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. 

Listed below are the five main strategies for increasing profit in 2021 using your ERP system and comprehensive financial reporting tools. 

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 analyzing 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 Enterprises 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. 

 

This allows sellers more versatility and, in certain cases, provides new business possibilities (via Amazon or eBay, for example), but that also makes it more difficult to get a clear picture of product revenue across platforms. When businesses use the automated reporting tools offered by each e-commerce platform provider, they get a much-distorted vision of their online business. Business executives will obtain consistent visibility into all their sales operations, through all sales channels, including e-commerce, by putting data together under one platform and then validating it so that it offers an apples-to-apples comparison. 

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 struggling market for business intelligence (BI) analysts and distributors. How can you determine 9 ways you are failing at Business Intelligence 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 “5 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, thinking about moving fast and breaking 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 high 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 convenient 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 annoying points. Your response to these issues will determine if your BI project succeeds. 

 

The two most common mistakes that BI newcomers 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 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. 

Identify these 9 ways you are failing at Business Intelligence and make a big shift with power of BI in a company with 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, to eliminate these 9 ways you are failing at business intelligence and lead your way to data driven insights.

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Power BI with Jet Analytics

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 systems used together; Power BI with Jet Analytics have the same overall goal: 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 the 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 various sources, not all accounting systems.

Benefits of Using Power BI with Jet

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.

 

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 Microsoft BI Power 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 or get a personalized training for yourself.

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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. By leveraging modern tools to optimize processes with data visualization, companies can transform complex datasets into actionable insights, enhancing decision-making efficiency across all departments. 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 unique outlook on data and a game-changing method for decision-making, compared to what was previously 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.

In addition to finance, operational and supply chain management teams benefit from these dynamic features. Inventory dashboards, for example, provide real-time insights into stock levels, supplier performance, and demand forecasting. This allows organizations to streamline their operations, reduce costs, and make informed decisions across departments. Integrating financial reports with operational data ensures a comprehensive view of business health, enhancing decision-making at both the strategic and operational levels.. 

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 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 visualization does this is by compressing large volumes of data into a readily available layout. 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 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 from 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 across the board, helping companies optimize processes with data visualization for better decision-making.

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 analysis will affect 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 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 analyze and predict cash flow. 

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 analyze data optimize cash flow analysis, and more. 

 

Review the Jet Sample: Cash Flow Statement.

 

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 make strategic business decisions. Cash predictions can be generated automatically using BI software. Financial managers can remain updated 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. 

 

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

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. Business Intelligence in Demand Forecasting is one of these fields where businesses extract information from existing data to assess purchasing patterns and predict future trends through predictive analytics.

 

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. 

 

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 software is designed to capture, unify, sort, tag, analyze, 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 analyze 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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ways to optimize your ERP reporting

How to Optimize Your ERP Reporting?

ways to optimize your ERP reporting

According to a recent study, nearly 81% of companies surveyed reported that they had either introduced the use of ERP software or were in the process of implementing it. So, what makes ERP reporting important? By leveraging ERP data analysis, businesses can create strategic plans, forecast future trends, and develop advanced strategies. To truly maximize these benefits, it’s essential to optimize your ERP reporting for more accurate insights and decision-making.

 

A depth of data indicates that financial reporting generates as much clarification as it creates confusion:

 

97% of CFO’s have uncertainty regarding the quality of reporting.

 

  • 40% of CFO’s are concerned that information is reliable and precise.
  • 87% of accountants function overtime to complete the financial closing.
  • 86% of finance teams say that their analytics are not informative.

The only downside is that companies cannot be successful if they don’t have reliable, accurate, and detailed ERP reporting, which can lead to them making risky choices without even acknowledging it. The plus side is that optimizing ERP reporting is not a difficult task in comparison to the usual reporting process.

 

Listed below are the 5 ways businesses can optimize their ERP Reporting to make it quick and easy:

Self-Service Reporting

Users often need to submit a request to IT before getting access to a report and wait in a queue until they can access it. Users must depend on technical experts because working with the underlying data is hard. For users who are not IT experts, self-service ERP reporting is intended to be user-friendly. This kind of reporting is less about the careful organization of data and more about being cost-effective and a time saver.

 

For instance, IKEA, one of the biggest retail company has enabled self-service ERP reporting after the implementation of Jet Reports and witnessed instant results. A report that may have taken hours for a warehouse manager can now be done within seconds. Time is saved by enabling self-sufficient ERP reporting.

Automated Processes

A large-scale data organization effort is required to report on finance and operations throughout different departments. The workload includes tracking information from different sources, transferring it from one document to another, and putting time and effort to arrange it all in one clear performance portrait. Advanced automated processes speed up this effort by automatically placing data from ERP systems and other networks, then placing it for immediate analysis into pre-built ERP report templates.

 

Amref Health Africa, a major NGO in Africa, was having difficulty handling data manually before adding Jet Reports to its reporting toolbox. Now the organization spends less time on handling information and reporting.

Flexibility

Reporting is a regular duty that changes with time. Depending on the same reports adds up to poor performance management, but it takes extra time and feedback from IT experts to produce customized reports. ERP reporting stops being a hassle when it is simple to track various metrics, rewrite reporting data, receive deep insight from reports into transferable data, and access real-time updates on request.

 

Using an ERP reporting tool, companies can keep track of their data in real-time. Fawaz Holding seized the benefit of customized reports when it introduced Jet Reports to operate side by side with its Microsoft Dynamics 365 Business Central ERP. By building flexibility into the processes, ERP reporting becomes easier.

Business Continuation

Accurate ERP reporting is vital after the global pandemic. Decision-makers instantly require quality, updated data, but it can also be made inaccessible by the same situation that makes it essential. ERP reporting should function at any time, providing the same robust functionality even though users are operating from elsewhere.

 

Similarly, Enova Facilities Management started to save time on ERP reporting using Jet Reports. When COVID-19 struck, the business utilized those time saved. The challenge didn’t sway the method of reporting, instead, it provided leaders greater insight into the situation.

Higher Standards

ERP reporting can be difficult when the processes are not automated. It leads to a lot of time and effort spent on manually documenting reports and generating analysis. Many ERP reporting systems allow the users data security. It is important to set high standards for data reporting, so businesses need to implement robust ERP systems to automate processes and receive greater insight into the workings of all departments.

 

Air Trade Centre, a Turkish electronics firm felt it needed quicker ERP reporting and relied on Jet Analytics as the solution. After that, reporting then demanded 60% less feedback overall, which reduced the time it took IT on reporting.

In Conclusion

Learn How to Optimize Your ERP Reporting as accurate reporting is a result of quality data, which is precisely the reason the process takes time. Data is an unruly commodity that takes an extra effort to control, protect, and manipulate. As the data volume grows, ERP reporting will fall behind and cause companies to delay acting. That is why it is important to search for strategies that make data as quickly available as possible by automation.

 

So, if you face any challenges in reporting, our experienced consultants can provide you with solutions to help you optimize your ERP reporting and make your business grow. Schedule a call to discuss your requirements. Contact us now.

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Risks to Your BI Implementation

Why BI Implementation Can Be Risky?

Risks to Your BI Implementation

Gartner recently published a study on all the stuff that can go wrong with your BI implementation. We have classified them into 8 different risks to your BI implementation based on our team’s insights here at Global Data 365. These risks can easily be overcome, but they are very likely to infiltrate your business plans. 

 

An analyst in Gartner’s report takes great pains to stress that there is far more risk associated with non-technology problems than there is with implementing infrastructure, resources, and applications. Listed below are the 8 different risks of BI Implementation; so you can recognize them and avoid potential problems in the future. 

-Building a Project with BI Implementation

Starting a business intelligence project with this mentality means that the program is funded by IT and is usually led from a technological or data-centric viewpoint. The issue is that BI Implementation is being driven by IT rather than the company. Unless IT has a strategic plan or a consumer case of their own to include here, they aren’t interested in the final consumption of the BI deliverable and can only play a minor part in the development. 

 

The solution is to ensure that the project team includes a marking scheme from the business side of the house from the start of the planning phase through infrastructure upgrades. 

- Excel Culture

The second potential risks can be Excel. With Excel, you collect data from an internal structure, load it into Excel, and manipulate the figures. Every single person who participates in this would have a different point of view for the BI Implementation. Different methods of converting numbers into metrics will be used. They may also have opposing goals. You’ll get different results from each, and your data will be totally inaccurate. To us, that just means one thing: risk. The company is at risk. It’s the danger that comes with making costly decisions based on inaccurate knowledge. 

 

The solution is to build a data warehouse. This will be the location where everyone has settled on the data that will be used to handle the company, as well as how that data will be combined with the methods that will be used to measure items like total revenue and net income. 

- Issues in Data Quality

Everyone deals with issues in data quality. The problems that trigger it are various, and their effect on business intelligence is important. This is because people would not use BI software based on data that is meaningless, incomplete, or suspicious. 

 

Establishing a process or collection of automated controls to detect bad data and prevent it from entering the data warehouse or BI environment is the solution. Surprisingly, a BI implementation can solve this problem all by itself. It’s because having data quality problems in a dashboard will draw attention to them. That should give you a good idea of how to track them down. Learn how to plan your data for business intelligence.

- Diverse Options

You’ll be confused if you search “BI solutions”, attend a related tradeshow, or read quite a lot of BI reports. There are several options available. But how do you know which approach to business intelligence or that the BI implementation is right for you? 

 

The solution is to avoid putting the cart before the horse. First, assess the requirements. Evaluate them from a market and a technological standpoint, and then use the results of that exercise to guide the quest for approaches and solution providers. 

- Using Existing IT Provider

BI is unlike any other project. Since you’re working with human beings and their methods, as well as the changing conditions of the business world, there’s a little luck involved. We are convinced that a business that specializes in BI projects will not be able to help you succeed. Seeking a business that specializes in BI environments is the safest approach. For this, you’ll need a professional. 

 

If you’ve decided that they have the technological experience and track record to make you happy, if you want to be good, don’t be afraid to evaluate them on fit, desire, and dedication. Those are the things that are more difficult to determine, but BI implementations usually last a long time, so it won’t cause you any problem.  

- Time in BI Implementation

The other threat is about the time it takes in your BI implementation. A BI project can be placed into a low-cost maintenance state, but your company will never stop evolving, and because BI is built to model your business, it must also change. 

 

Having demands is one way to avoid this from being a concern. You should anticipate that the BI success would be a moving target over time. Let everyone know how things will pan out. Prepare for it by scheduling deliverables and budgeting for it. 

- Insufficient Training

Many companies spend all their BI budgets on software applications and a few weeks of user training. Today’s BI systems, on the other hand, are dynamic constructs that need much more training for users to derive true value from them. Besides, continuous training is needed to ensure that users are familiar with and comfortable with the system. 

 

Furthermore, companies should ensure that the software they install contains online training videos that help users become more comfortable with the current BI framework or the companies should opt for online training of the BI Software they use. 

- Data Collection from BI software

Some businesses gather useful data from their business intelligence tools but don’t distribute, evaluate, or act on it. When deciding what to do with BI implementation, it’s important to think outside the box. Companies may avoid risk and make educated decisions to move their industry forward by using the knowledge collected and adapting it to their own business models. 

Companies can use BI software on different data points, analyze risks, and predict trends. To improve the reporting capabilities of their BI software, companies should be able to identify risks and predict trends. 

Having a Strategy

Not having a BI strategy can be one of the biggest threat to your BI implementation. BI strategy can change the way you collect, analyze, and deliver data. As everyone works on the same KPIs to drive action and optimize processes, there is no chance of manual error. 

 

Global Data 365 It helps you with its experienced team who considers all the potential risks and avoids them during your BI implementation. To discuss your requirement, speak to one of our BI experts. 

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Limitations of Power BI

Limitations of Power BI – Are They Risky?

Limitations of Power BI

If your business is considering implementing Microsoft’s Power BI analytics framework, you must understand the level of complexity and limitations of Power BI involved in successful integration. Power BI is a many-month software project based on a complex mix of technological elements, not just a device you install and customize. To get it right, you’ll need a lot of preparation and the highest level of management skills. So, what is Power BI and what are some limitations of Power BI?

Power BI

Microsoft’s Power BI is a cloud-based business intelligence service package. It uses insightful visualizations and tables to transform raw data into usable information. Data can be processed and used to make strategic business decisions in a short amount of time. Power BI is a set of business intelligence and data visualization tools that includes software services, applications, and data connectors. Power BI is a user-friendly tool with versatile drag-and-drop design and self-service capabilities. Power BI can be used on both on-premises and cloud systems.

So, what are the limitations of Power BI that you can avoid?

What is Jet Reports?

Jet Reports, on the other hand, is a dynamic business intelligence tool that goes beyond conventional financial reporting. With its user-friendly interface and Jet Dashboard Designer, organizations can leverage its capabilities for comprehensive financial reporting and analysis. Jet Reports is known for its adaptability and ease of use, making it an asset for businesses aiming to enhance their reporting processes. 

We are going to give you three scenarios where a user should consider switching to Jet Reports or Jet Analytics: 

Complexity Involved with Power BI

Most of us have become used to applications that can be downloaded in minutes or even hours in the case of more advanced systems. That’s a fairly straightforward scenario. At the other side of the curve are items that entail some configuration and are designed and implemented by a team of specialized experts to overcome the limitations of Power BI. A full Power BI implementation must solve a slew of design issues. The answers to those questions will affect efficiency, productivity, and adaptability in the long run. Some of the major differences between a Power BI cloud deployment and an on-premise deployment. For instance:

 

– What features should you run, where should they run, and how will they all interact?

 

– What level (or levels) of security do you incorporate?

 

– Will you be using SQL Server Analysis Services to model your results, or will you use the Power BI desktop tool?

 

– Should you use Power BI’s Direct Query function or import data?

 

– Will a gateway component be needed, and if so, where will it be installed?

 

All these are technical questions, but the solutions have long-term consequences, and it’s always difficult to adjust later. This level of complexity necessitates upkeep, which entails additional costs and disruption.

Power BI: Toolset not a Complete Solution

There are no reports included with Power BI out of the box. In fact, Power BI reporting necessitates a substantial upfront expenditure, not just in terms of constructing the technological infrastructure, but also in terms of deciding how you access the data, how and when data must be converted or pre-processed, where you archive them, and so on. After you have answered those design considerations and limitations of Power BI, you will need to put in a lot of time to set up the data access and data flow.

 

Data access is becoming more complex in this age of cloud computing. This is particularly true of Microsoft Dynamics 365 products, which no longer require unlimited reporting access. Microsoft has suggested some possible workarounds, but all of them require major compromises. Microsoft has introduced an indirect layer of “data entities” in Microsoft Dynamics 365 Finance & Supply Chain Management (D365 F&SCM), for instance, that developers can use to obtain entry to ERP data. Personalizing Power BI can be very costly. Since every company is different and has its own set of requirements, customization is unavoidable. Recurring costs arise from the ongoing maintenance of such customizations.

Power BI as a Dashboard Visualization Tool

Power BI was developed to be used as a dashboard visualization tool. It does an adequate job of producing conventional tabular reports, lists of individual records with several columns and subtotals, and it does a great job of providing an insightful visual analysis of what is happening in the market. Traditional banking statements are not generated by Power BI because they are somewhat different from other forms of reports. Some more limitations of Power BI such as Filtering, masking, or grouping GL sums by account column, for example, is commonly required when creating a P&L statement. This is often done in different ways for each row in the report.

 

Columns in the report may be sorted by organizational agency or division, or they can be used to reflect various time spans, budget vs. real, or variance amounts or percentages. Since Limitations of Power BI has a little method of controlling such distinctions, having it generate a comparatively straightforward P&L is a very costly custom programming activity.

Power BI without the Limitations

Global Data 365 offers self-service, user-friendly analytics and reporting tools, as well as collaboration with Power BI and Excel. With the help of Jet Analytics, we hold the guesswork out of Power BI by automating the process of developing a data warehouse with pre-built connectors for over 140 different ERP systems, allowing business leaders and analysts to have the data they demand, when they need it, without any need for specific commands or the complexity and limitations of Power BI stack.

 

Need to overcome the limitations of Power BI, opt for our Power BI Training program today.

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Global Data 365 is composed of highly skilled professionals who specialize in streamlining the data and automate the reporting process through the utilization of various business intelligence tools.

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