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AVOID 3 COMMON MISTAKES THAT CAUSE BUSINESS INTELLIGENCE PROJECT FAILURESave Your Microsoft Dynamics NAV BI Project

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AVOID 3 COMMON MISTAKES THAT CAUSE BUSINESS INTELLIGENCE PROJECT FAILURE

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Table of Contents

Business Intelligence Solutions for Dynamics NAV 3

4 Haunting Statistics of Business Intelligence Projects Gone Wrong 4

What is Data Warehouse Automation? 5

Why Do BI Projects Fail? 7

Technical Code Creation 8

Manual Data Mapping 8

Organizational Alignment 8

Top 6 Benefits of Data Warehouse Automation (DWA) 9

Build Your Data Warehouse with Jet Reports 15



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BUSINESS INTELLIGENCE SOLUTIONS FOR DYNAMICS NAVMicrosoft Dynamics NAV is one of the most installed mid-market enterprise resource planning (ERP) systems in the world. With over 130,000 customers, it is a robust and flexible open software platform with a simple interface designed for development and longevity. Although it comes with a pile of reporting and business intelligence (BI) options suitable for all industries, users still have a lot of trouble accessing their data and customizing reports.

What’s our real financial standing? How much are we spending? Where does our revenue come from? If any of these questions still leave you scratching your head, there are plenty of solutions out there to help you answer them. These solutions can help you create, format and use the reporting available from Dynamics NAV in an easy-to-understand format for your everyday user.

But let’s take a step back and talk about the logistics of actually implementing business intelligence.



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4 HAUNTING STATISTICS OF BUSINESS INTELLIGENCE PROJECTS GONE WRONGDelayed projects, growing costs and misaligned expectations have been longstanding problems with business management and analytics software implementations. An independent study completed by Panorama Consulting Solutions in 2017 shares the following data collected on software implementations:

• With the average project cost totaling $1.3M, a whopping 74% of survey respondents experienced cost overages

• The average implementation time is 16.9 months, but 59% of respondents recorded project delays and missed deadlines

• 56% of respondents experienced operational disruption

• 37% believe that they received 50% or less of the software benefits promised to them

Your Dynamics NAV solution includes BI tools like the Role Center, built-in report designer, analysis views, Microsoft Server Reporting Services (SQLSRS) and SharePoint – but they all require an investment of time, money and resources to make it fit your business operations and data goals. These statistics show that there is a lot of room for error when it comes to the processes required to implement software.

For business intelligence and analytics software specifically, you need a “centralized nerve center” provided by the organization’s data warehouse to make your data usable (The Data Warehouse Institute, n.d.). There are traditional approaches to this that are heavy on manual code creation and testing - or you can choose a data warehouse automation platform. This whitepaper focuses on a fast and cost-effective delivery solution to simplify data warehouse design, development and deployment – leading to the successful adoption of business intelligence in your organization.



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The Data Warehouse Institute (TDWI) defines business intelligence as, “The processes, technologies, and tools needed to turn data into information, information into knowledge, and knowledge into plans that drive profitable business actions.” A well-implemented data warehouse provides much of the foundation that enables BI to transform data into usable, actionable information for your business.

Data warehouse automation (DWA) is a technology and approach designed to build data warehouses efficiently. It reduces resources, costs and project risk by automating your entire data warehousing life cycle from planning, analysis, design and development to operations, maintenance and change management.

The DWA concept has a distinct parallel to manufacturing, where about 100 years ago—thank you, Henry Ford—we realized that there were parts of many processes that demanded automation. Time and money were saved immediately. Efficiency went up and product quality improved.

WHAT IS DATA WAREHOUSE AUTOMATION?

Building your BI solution is no different. The parts of the data warehouse lifecycle that demand automation are repetitive, labor intensive and time-consuming, like:

• Writing SQL code by hand

• Performing QA cycles

• Manual data mapping

• Extensive documentation

The idea behind DWA is that if you can automate these time-consuming tasks, then your project team can focus on the components that require more intellectual input than raw technological horsepower. In fact, supporters of DWA claim that using it will accomplish an initial BI implementation up to five times faster than traditional methods. This results in a higher success rate for BI projects, and most importantly, it allows for faster, better and more cost-effective delivery of BI output to the business.



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PROJECT PLANNING

DIMENSIONALMODELLING

BI APPLICATION SPECIFICATION

PROJECT MANAGEMENT

BI APPLICATION DEVELOPMENT

DEPLOYMENT

GROWTH

MAINTENANCE

TECHNICAL ARCHITECTURE

DESIGN

PRODUCT SELECTION & INSTALLATION

PHYSICAL DESIGN ETL DESIGN & DEVELOPMENT

BUSINESS REQUIREMENTS

DEFINITION

THE DATA WAREHOUSE AUTOMATION ANDBUSINESS INTELLIGENCE LIFECYCLE



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WHY DO BI PROJECTS FAIL?One of the widely accepted pitfalls of traditional data warehousing methodology has been that building a BI project is a long, tiring and expensive process. DWA offers a solution to that, by changing the way we think about building a data warehouse. The expected practice of extensive up-front analysis, design and modeling is left behind. The mindset changes from ‘get it right the first time’ to ‘develop fast and develop frequently.’

The reasons why most BI projects fail are a result of the traditional data warehousing approach. Here are three of the most common reasons for extended timelines, increased expenditures and general dissatisfaction:



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1. Manual Data MappingData is messy. Any large data set is guaranteed to have gaps, errors, and duplications, among other atrocities. These need to be discovered, understood and rectified before the data can get used. This exercise often takes longer than expected because there is usually a need to combine several data sets in order to get a full view of company operations.

For example, combining CRM information (the date a sales opportunity was entered) with the ERP Financial module (the date a first invoice was posted) will give you sales cycle times and enable financial projections. Now there are two messy data sets to deal with, and in the real world we usually end up dealing with many more. This is a great example of a time consuming, repetitive task, that doesn’t require human creativity and is better accomplished through automation.

A typical multi-database scenario involves trying to get data from various source systems to match. One system records a specific type of revenue transaction, but it may not be the system of record for the company, and as it turns out, has a different chart of accounts structure. For the revenue transactions to flow into the correct revenue accounts, a mapping exercise must take place. If you were using traditional methods, you would need to write and maintain SQL code to handle this mapping in addition to manually documenting any and all changes for data audits.

2. Technical Code CreationBuilding a data warehouse and set of OLAP cubes is largely an effort in writing masses of SQL code. Code is what moves data from a source system, like Dynamics NAV, to a target system, like a data warehouse. Code is used to define metrics, create data structures like product hierarchies, and conduct calculations both simple and complex.

| Building a data warehouse with manual code is time-consuming, resource heavy and error-prone.

For example, it can take a skilled SQL programmer several hours to move a single field from a source database to a target destination.

3. Organizational Alignment A shared vision and understanding of your data must be created to deliver a BI product that people will actually use. And this is often the hardest and most time consuming of all tasks. It is vitally important to get everybody on the same page about what data is important and how it is to be consumed. Everyone must understand and agree which individual pieces of data will come together to tell the story of the organization and, how it is operating. For example, it doesn’t really matter if gross profit is defined as Sales minus COGS, or if it is defined as sales minus COGS plus SGA. What matters is that everyone comes to an agreement on the formula.



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TOP 6 BENEFITS OF DATA WAREHOUSE AUTOMATION (DWA)DWA can change more than the way you look at your business, it can change how you do business. Here are six reasons why using DWA can help you successfully adopt BI in your organization and avoid costly project delays and failure.



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1. Automates SQL Code Creation

You can think of any data warehouse automation platform as a code-generating machine. Instead of writing a block of SQL code, you can use a mouse click. That simple click generates a substantial amount of code which compiles in the background - in this case, a SQL Server Integration Services Transfer Package to move a field from the source database into a data warehouse.

The same underlying tools and processes are used as if it was done by hand, but the difference is that it takes about a second to complete the operation instead of an hour, or more, of coding. The raw speed advantage is obvious, but since the process is programmatic, i.e., done by a machine the same way every time, human error is eliminated, testing time is greatly reduced and re-working the code to fix errors is not necessary. Time and money are saved, and results are delivered faster.

2. Eliminates Manual Data Entry

Going back to the multi-database scenario where you have to get data from various source systems to match, data warehouse automation would do this in a single click. Instead of the traditional way which requires an experienced resource to write and maintain SQL code, the code would generate in the background – in seconds. It is the same for other field transformation tasks, scheduling jobs and generating documentation – all are candidates for automation.

Because of the way it generates mountains of SQL code with the click of a mouse, DWA lets one person do the work of five. It allows you to stop paying people to do something as mind-numbing as writing SSIS scripts. Most importantly, it puts information into the hands of business people five times faster than before.




3. Creates a Shared Vision Between Business Users and IT

DWA allows you to combine disparate pieces of data quickly, take them through a complete BI development cycle and deliver results to the business to see if it works. This exercise would be unthinkable in the traditional model because it would take weeks, if not months to do. With DWA, this can be completed in hours, and in essence, it allows you to fail fast. Results can be tested by business users immediately and changed quickly if they are incorrect.

At its’ core, DWA allows BI teams to forget about the laborious, time consuming, hands-on work and focus on the ideas. More time is available to work with the business users to find out what information will really make a difference. What KPI’s do they need to catch a trend early? What process change will cut days out of their reporting cycle? How can corporate data be used to save the company time and money? DWA will likely cause you to stop thinking about IT and business folks as two different groups. They end up in the same room so often, talking about results, that they start to form a cohesive team with a collaborative view.

Instead of stark and abstract requirements gathering sessions with a long wait time afterward, you have workshop style meetings where business users are communicating, and those ideas get turned into reports and dashboards right in front of them. This iterative style of building BI turns the task of maintenance into a continuation of development. Since it is rare that anybody really knows 100% of their requirements, this method supports the uncertain and changing reality of the business world.




4. Mitigates Risk

Every IT project has risk associated with it: Risk of delayed project completion; risk of going over budget; risk of low user adoption. In short, it is all about the risk of wasting your organizations valuable time and money. Using the traditional method of building BI, the time it takes to create code, verify data, and align metrics, can result in all kinds of unanticipated issues.

In the DWA world, the technology part happens so quickly; it changes the way business intelligence projects get built. The traditional requirements gathering phase morphs into more of a priority setting exercise. This happens because virtually any idea that comes from the business users can be put into effect without a monster effort. Business users’ needs are collected, prioritized and then ‘time-boxed.’ This means that priority number one is evaluated and an estimate is given for how long it will take to build – a day, five days or 10 hours.

You can think of each delivery cycle as not only short and quickly followed by another one, but also as its own individual event. The success or failure of the project does not depend upon or affect any other delivery cycle. This means that business users can begin using the most important deliverables as soon as they are ready, while eagerly waiting for the next set to land in their laps.




5. Delivers Rapid Time to Value

Maybe that is what is most intriguing about the promise of DWA: it is a technology that solves long standing problems and has a ripple effect into non-technology issues. It allows us to get to what is important from a business intelligence project: the ability to respond quickly to changing business conditions. Business users are getting what they want, when they want it, as opposed to what they asked for six months ago. Rapid time-to-value is consistently realized since new BI and analytic functionality can be delivered in days, or even hours, instead of months.

Shorter implementation times, faster delivery and easier maintenance mean lower costs and a quicker return.

6. Fulfills User Expectations

Business users have expectations that what is promised will be delivered. They need data in a usable format in order to make decisions. Accounts Payable must have accurate information daily to keep the cash coming in. Sales and Purchasing have to know what is in inventory to sell and replenish stocks. If these capabilities are not delivered as promised, you are creating risk on multiple fronts.

The shift to DWA enables business users to get what they are asking for very quickly, decide if it is right, and then move on to the next thing. It also accommodates change much better because it doesn’t force the development team to ‘lock down the code’ and declare, “No more changes.” Change is so easy to implement, it becomes part of the process.




DWA is not just a better, cheaper, faster way to build a data warehouse. By its very nature, it changes the way we work. Like true innovation should, it builds on itself to transform our habits and our way of thinking. It changes the things we focus on – we focus on business issues – not technology. It inspires productivity and it produces results.

HOW TO CHOOSE A BI SOLUTION WITH PROVEN ROI THAT’S EASY TO IMPLEMENT AND USE.The right BI solution for your business and Microsoft Dynamics NAV system should be easy to use, flexible, and built for your business users. To help you select the right analytics software, we’ve put together a short but comprehensive webinar on how to choose a BI solution for your Microsoft Dynamics-run business. In this webinar, you will learn:

• What you need in a BI solution

• What to ask a BI solution provider

• What to expect from implementation

• Report and dashboard distribution options

WATCH WEBINAR NOW


https://www.jetreports.com/webinar/finding-right-business-intelligence-solution-company/?utm_source=jetreports.com&utm_medium=pdf&utm_campaign=avoid-3-common-bi-mistakes-nav&utm_term=jet-reports&utm_content=cta



BI CUBES

• Per subject • Performance • Metadata

DATA WAREHOUSE

• Relevant data • Cleansed data • Multiple sources

DATABASE (S)

• 1,000+ tables • 10,000+ fields • Complex data model

COMPLEX

NAVCurrent

CRM

NAVUpgrade

LegacySystem

SIMPLIFIED

BUILD YOUR DATA WAREHOUSE WITH JET REPORTSWhen most businesses are asked about their current level of insight into their operations, business intelligence solutions are a future thought. They want to get there but they don’t necessarily want to go through all the steps required to achieve intelligent reporting Thankfully, technology has evolved, and you can begin using a solution right away that is fully compatible with NAV and easy to deploy.




SCHEDULE A DEMO OF JET REPORTS FOR DYNAMICS NAV

Your Dynamics NAV system has a great foundation for reporting and business analytics, which is why we’ve designed our products specifically to work for it. Using Jet Reports as your third party BI solution, we take your complex database and

simplify it – so your Dynamics NAV users can design powerful and insightful reports in an Excel-based environment on their own.

Our solutions are specifically built for Dynamics NAV end users and work immediately out of the box, cutting your costs by 50%. Take the first step towards effective change and tangible BI results and see what Jet Reports can bring to your business.

See for yourself why 11,300 customers from 94 countries trust Jet Reports to manage their Microsoft Dynamics NAV analytics.

SCHEDULE A DEMO OF JET REPORTS


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