How Can the Systems Integrator Channel Make Money with Data Integration?

Data Integration is Fundamental

Data integration is fundamental when companies use more than one system. Data integration is the process of transferring data located in various data sources to other data targets. Data integration and collaboration between data systems and processes is vital because it allows processes to work faster and be more reliable and robust. The alternative is manual re-keying of large amounts of data which is practically impossible at this phase of our economy. By integrating systems like Enterprise Resource Planning (ERP), Material Requirements Planning (MRP), Supply Chain Management (SCM), Quality Management System (QMS), and the like, a company can reduce errors and human touch through majority of the processes of a company.

Every company needs data integration because it will make the company competitive. Consider a company using for CRM, MS Dynamics Great Plains for accounting, PayPal for receiving payments. The company sales team feeds the data into the CRM solution as sales information. The data then has to be converted into Invoices in MS Dynamics GP upon sales completion. The generated invoices will be paid for by the customers using PayPal. The payments from PayPal then have to come back into the MS Dynamics GP accounting system. In this scenario, three different systems are involved in the process and people may manually create the customer information, invoices, payments and other information in the systems.  This can limit the growth of the firm compared to competitors. Full data integration is possible and can give a competitive advantage to a firm that is fully integrated.

Needed in Projects

Data conversion and integration is a significant requirement when a company is moving to a new system. The project would need existing and historical data to be pushed in to the new system.  A typical example would be, companies using QuickBooks Desktop for accounting who want to migrate to any other accounting systems such as Netsuite, Xero, or other systems. In this case, the existing accounting and historical data should be moved to the new accounting system as a pre-condition to going live. Getting this wrong would add a lot of risk to the project itself.  A good data integration tool can help the systems integrator reduce the risk of this aspect of the project dramatically.

Almost all projects need to create mechanisms to move back and forth between systems. Data integration processes that work continuously after the project goes live have to be designed and implemented. For example, a company may be selling products using multiple channels, one of which is online.   Shopify could be the online ecommerce software while Intacct can be the accounting system where direct sales are logged. Here, data synchronization may be required to keep the available product quantity accurate between multiple systems.   Many vendors write special code to make this happen or let the customers do it manually via uploads. This creates a long term administrative nightmare and leads to errors in the future.   A solid data integration tool can keep the data in sync accurately.

Not Doing Data Integration is Risky

Data integration is a risk often overlooked by companies when they initiate a new project. Their focus will be on the new system’s feature functionality and they would pay less importance to the initial data conversion or the subsequent continuous data integration process.

Some of the risks can include:

-          Missing historical data

-          Poor quality of source system data

-          Undocumented adjustments and changes to data

-          Poor definition of requirements related to data

-          Not sizing the data conversion and data integration part of the project

-          Lack of clarity of responsibility for data integration and data conversion

-          Effort and budget runs over estimates

Software projects fail frequently and more than 31% of projects get cancelled outright.  A large number of projects go over budget. Many of the reasons for failure get directly assigned to the Systems Integrator.  As is, obvious data integration can underlie many of the failure reasons. article 1

What Makes a Suitable Integration Tool

When a systems integrator selects a data integration tool, it needs to consider a number of selection criteria.

A key criterion for vendor selection is systems compatibility. The selected tool must foremost be able to interact with the specific systems that the customer's company uses in the project under consideration. Companies look at whether the system you offer is interoperable with theirs and how much it automates the daily process and avoids manual processes. The tool must have the ability to create a connection to the systems under consideration with the proper security and authentication. Alternatively, it must be able to take data output from those systems or provide data as files to be consumed.  The tool should also have clear understanding of the data models in the respective systems, or the systems themselves should be able to provide descriptive data models to the tool.  Many systems such as can provide a complete scheme of their data model to the integration tool.

In addition, good tools must have the following:


1.     Connectivity to standard formats normally used such as MS Excel, Text files, CSV files.  It is very common for systems to provide data and consume data in the form of Excel files, flat or CSV files. Almost all systems will accept a text file format of CSV or comma-delimited text files.

2.     Standard open protocols such as ODBC (Open Database Connectivity) to access relational databases. Almost all databases can be accessed using ODBC.  And even some applications, such as QuickBooks, are accessed using third party tools that comply with the ODBC standard.

3.     Connectivity to popular platforms. A data integration system should support the most common applications customers use. These are the three classes of the most common applications: ERP, CRM and Ecommerce. Example applications include MS Dynamics AX, SugarCRM, and Magento.

4.     Data quality checking and correction.  This is also known as error recycling. The process should have the ability to categorize informational notices, warnings, and fatal errors. The system can present the errors and warnings to the user and allow to rectify them easily.

5.     Scheduling of execution.  Without manual intervention, data integration will be executed automatically in the scheduled time. This can be achieved by scheduling the data integration process every hour. Scheduling can be real-time or on a periodic basis. A typical example: Closed opportunities in should be exported as invoices to MS Dynamics GP every hour.

6.     Application Programming Interface. Some of the most promising innovations going on right now in integration include the ability to connect using application programming interfaces (APIs). APIs determine how applications will interact with other applications. 

Good integration tools reduce the systems integrators time during the project. They avoid unpleasant surprises to the customer such as delayed projects or cost overruns.

How to Make Money with Data Integration

Unfortunately, most companies do not fully understand the importance and value of integration services. Consequently, they are less inclined to pay a lot of money for this portion of the project proposal.  To get all the benefits of a successful project plus make a good profit, the following are recommended:

1.     Select an affordable data integration solution such as  The price point for the product should be low enough to allow you to make more money. Make sure the product has enough commissions or the ability markup to make up for the services that may not get paid by the customer.

2.     Call out every integration task in the initial proposal and project plan. This is very important.

3.     Break up conversion and integration tasks by table and make visible to the project team.

4.     Break up conversion tasks so that the production of source data can done by customer’s in-house resources to reduce unnecessary budget inflation. Many customers prefer this. Associate delivery dates to these tasks so they are also held accountable.

5.     Get customers assigned to data validation of results after conversion or integration and save budget dollars that can be used for other services.

6.     Have customers sign off on the conversion and data integration phase, so they see the importance of those tasks.

With some foresight, this can add to the profitability of the project for the systems integrator channel.