Integrated Business System.

A business system consists of software tools that track, drive and measure business processes.

On average, most businesses will have more than 80 software solutions that make up their business system. These systems will capture data used to track and manage your business processes.

In an integrated business system, all these tools work together.

Data must flow through the business. Through departments and processes and across silos. Through software systems. Recording activity and driving processes. How well this data flows will determine how integrated your systems perform.

Systems built on individual tools with little or no automatic integration will be inefficient. They will add cost to delivery and inefficiencies. They will lead to poor data quality.

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How do you review and measure your system integration

You start by following your data, identifying the processes involved, the systems used, and the data storage engaged for each step.

Remember, every individual spreadsheet used along the way is a system in its own right.

Selecting Technology Solutions

When selecting a solution, the focus is often on suitability, security, audit trails, etc. At Intelidat, we start with the Data.

Where an application stores the data is a crucial question.

68% of organisations say disparate data negatively impacts their organisation

Not just the standard questions about security and backup. The most important question for the business; how will that data storage fit into the data flow of your existing integrated business solution?

The critical stakeholder in this decision is the business

Far too often, this business voice is not represented. Instead, decisions are driven by department personnel who lack a holistic view of the business outside their immediate departmental needs. IT teams will be called on for specialist technology advice, but they are not asked about the effect on other processes and systems. That is the role of the Chief Information Officer. This is someone who speaks for the business rather than a specific department or IT.

They need to ask the business questions of the proposed technology or solution;

  • Do the benefits to that team outweigh potential detrimental effects on other teams, departments, or the business as a whole?
  • Will that solution help break down silo barriers or make them more difficult to cross?

Data storage in technology solutions

Each of these tools will store data. This storage is the beginning of your Data Stack. We call this the Data Source, which is the first stage of the Data Stack.

What is the Data Stack? Click here to read more about the Modern Data Stack

The data source is the data captured, enhanced and manipulated by the tools you use to deliver your Business System.

Your business will use these tools to capture, enhance and manipulate your data.

These will include tools such as your CRM, Marketing Automation, E-Commerce, and ERP. You may have additional sales invoicing, order fulfilment, financial tracking and reconciliation tools and finally, your accounts software.

These may be SaaS, Desktop, and bespoke solutions. Where they store their data will form part of your Data Source.

  • Can you access the raw data?
  • Can you extract data?
  • Can you update and enhance that data from external data sources?
  • Is the data source compatible with your data stack

Unfortunately, these questions rarely form part of the selection criteria. Yet they are likely the most fundamental long term issues you will face.

A major cause of poor data quality and inefficiency are business silos. Processes may run within departmental silos, but business systems should be independent of these silos.

A good business system helps your users do their daily tasks more efficiently. It will capture data and help drive your business process. It will encourage and ensure best practices and enable sharing information across the business.

Data should be entered once, used many times.

Business systems should be efficient, scalable and deliver good quality data.

The most basic principle to remember is that data should be entered once and used many times. Every time data is recaptured or has to be rekeyed, is an opportunity to introduce data quality errors.

This principle should not be restricted to any one software solution. It is the key principle to building an Integrated Business System. Data should only be entered once. Every time you need to rekey data into the same or a different system is a point of inefficiency. This applies across the business, not just within any individual software solution.

As an example, consider the following scenario:

A prospective client’s details (name, address and telephone number) is captured by the Sales or Marketing team and stored and maintained in their CRM software. The prospect becomes a client, and their details are needed by other departments for invoicing, fulfilment, and delivery, before being added to your accounts software.

  • How do the client’s details get passed along this departmental chain?
  • What happens when those details change? Are all departments required to manage their own changes?
  • Which department holds the master list of clients and how can you ensure all details are up to date.
    • Sales CRM
    • Sales Daybook
    • Delivery System
    • Accounts Software

This example raises questions beyond data entry. Capturing data is not just about tracking information. It raises the potential to drive processes- why did the act of making or recording the sale not prepare entries in all other systems?

One of the tenets of quality data is that it is consistent across a business. The list of clients recognised by the Sales and Marketing team should be consistent with the same list used by the Accounts team.

Your Data Governance Strategy determines the location of the master list. This dictates how data is named, stored, processed and shared across the business..

These rules should be followed across the business landscape.

Ask yourself…

  • Are your systems integrated?

  • When did you last review your data flow?

  • Could your systems improve efficiency?

  • Do you have data quality issues?

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