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How can IT be removed from Financial Reporting

Home > Blogs > How can IT be removed from Financial Reporting?

How can IT be removed from Financial Reporting?

July 26, 2021

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.

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.

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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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Risks to Your BI Implementation

Home > Blogs > Why Implementation Can Be Risky?

Why BI Implementation Can Be Risky?

May 21, 2021

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.

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 9 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 9 different risks so you can recognize them and avoid potential problems in the future.

Building a BI Project

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 it 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. 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.

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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 setting 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 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 are more difficult to determine, but BI projects 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 of 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, 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 helps you with its experienced team who takes into account all the potential risks and avoid them during your BI implementation. To discuss your requirement, speak to one of our BI experts. 

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Why Is Good Data Management Essential For Data Analytics

Home > BlogsWhy Is Good Data Management Essential For Data Analytics?

Why Is Good Data Management Essential For Data Analytics?

May 21, 2021

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.

Why Is Good Data Management Essential For Data Analytics

Today, Businesses have more data at their disposal than ever before. Over time, businesses that can efficiently use data as a strategic advantage can eventually achieve a competitive edge and outperform their rivals. Business administrators, on the other hand, must add order to the chaotic world of various data sources and data models to do this. Data management is the general term for this method. Data management is becoming an essential component in successful business management as the amount of available data grows.

On the other hand, a lack of effective data protection can lead to incompatible or unreliable data sources, as well as data quality issues. These challenges can hinder an organization’s ability to derive value from data-driven insights, recognize patterns, and spot problems before they become major issues. Worse, bad data management can lead to managers making decisions based on incorrect assumptions.

Availability of Data

The emergence of systems, such as ERP, CRM, e-commerce, or specialized industry-specific applications, is causing such problems. When you add web analytics, digital marketing automation, and social media to the mix, the data volume skyrockets. When you add in external data from vendors and service providers, it becomes unmanageable.

Many businesses understand the importance of using externally sourced third-party data to supplement and extend the context of knowledge they already have. However, it’s difficult to imagine taking that step without first having a grasp on the organization’s current data. Bringing all of this uncertainty under control is a key first step in implementing a strategic data analytics program. That is a two-step method from a high-level perspective. To begin, you must collect all of the data and store it in a centralized location. This includes filtering, transforming, and harmonizing data so that it blends to form a coherent whole.

Secondly, the data must be available to users around the enterprise so that you can put it to good use and add value to the company. In other words, you must implement processes that allow users within the organization to access the information easily, efficiently, and with enough versatility that they can evaluate and innovate without extensive IT training. To ensure efficiency, you must identify and implement these two aspects of data management individually. Flexibility and usability result from a pre-built data management process and interface; the quicker you assemble and clean up the data, the easier the data will start producing value for the business.

Multiple Systems

When a company runs several processes, data processing becomes a problem. As previously stated, this may include ERP, CRM, e-commerce, or any other software framework. It’s also usual for many companies to use several systems to accomplish the same job. Different ERPs may be used by different divisions or corporate agencies operating under the same corporate name. This is especially true when it comes to mergers and acquisitions.

Many businesses would like to perform reports against historical data stored in a defunct database. Since migrating accurate transactional data to a new ERP system is not always feasible, many companies use a workaround or simply go without, leaving important legacy data out of their existing reporting systems. Multiple data models are invariably present when multiple software systems are involved. A clear report detailing all of the company’s customers becomes a little more complex. If one ERP system has different tables for clients and vendors, while the other merges them into a single table (using a single field to classify them as customers, vendors, or both). Before loading data into a centralized repository with a uniform approach of the customer, you’ll need to extract and transform data from those two ERP systems. The process must include a type of translation in which data structures and semantic models are aligned.

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Extracting, Transforming, and Loading Data

The term “ETL” refers to the method of processing, converting, and loading data into a central repository. ETL is one of the most important aspects of a data warehouse, and it’s necessary for businesses who want to provide dependable, scalable, and reliable reporting. A data warehouse that embraces a complete view of data from across the enterprise, irrespective of which system it came from, is the end product of a very well ETL process.

This procedure often connects records that are spread through different systems. It is normal, for example, to designate master records with unique identifiers that aren’t always consistent across two or more systems. The central repository must link those two documents and classify them as the same individual to create reports that provide a full image of that customer.

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 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.

Self-Service Reporting and Data Visualization

The second important aspect of good data management is to make information readily available to users across the enterprise. Provide them with resources that allow them to innovate and add value to the company. In fact, data visualization tools are becoming a strong tool for informing, aligning, and encouraging leaders across entire organizations. Data visualization tools are now simpler to deploy, maintain, and use than ever before.

Until recently, installing and maintaining a data warehouse facilitated a significant investment in highly specialized technical services. A reliable computing infrastructure capable of handling the necessary workloads. Legacy tools necessitated a thorough understanding of the source data as well as meticulous preparation ahead of time to decide how to use the resulting data. Modern data visualization tools are extremely efficient and adaptable, requiring far less advanced IT knowledge. Many of the tasks associated with designing dashboards, graphs, and other visualizations can now be performed by frontline users who communicate with the data daily.

Data Management with Jet Analytics

Both aspects of the data management process as described here, are provided by Jet Analytics from Global Data 365. For starters, it offers a robust framework for constructing a data warehouse. With developing and managing the ETL method, bringing data from various fragmented systems under one roof for simple, relevant reporting and analysis. Along with that, Jet Analytics provides a robust reporting package that allows practically everyone in the company to create powerful visual dashboards, analyses, and ad hoc analysis.

To find out more about how Jet Analytics can help your company manage the complexity of multiple data sources, contact us.

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