Data and Integrity
Everyday, everyone, everywhere is bombarded by data. Nowhere is this more evident and important than in business. Who cares, or why should anyone care, about data? When operating and working in a successful company, data is a vital piece of the business success equation. More than likely, you are an important part of such a company, thus, you should care about data
What is Data ?
What is data exactly? If you asked different people this question, you would get multiple answers. A couple typical definitions are as follows:
Facts and statistics collected together for reference or analysis.
Things known as facts, making the basis of reasoning, calculation and decision making.
An example of business data is “the number of company products sold in the southeast territory in the previous business quarter.” There is one correct number that fits this criteria and is our “fact” within the definition of data. This fact can be referenced for analysis and can be the basis for making a business decision.
Why is Data and It’s Integrity Important ?
Who cares if data is incorrect or if the overall quality is poor? Data quality is referred to as “data integrity.” It is maintaining and assuring the accuracy and consistency of data over its entire life-cycle. Data integrity means that the data is accurate and reliable. At various levels, all company employees make business decisions to assist in their roles and responsibilities which ultimately contribute in the company’s success or lack thereof. In most companies, there are areas where important business decisions are routinely made based on data. Examples are as follows using the “number of company products sold in the south east territory in the previous business quarter” data example above:
Business Performance Measurement.
Consistently measuring business performance against company goals and the competition is imperative for success.
Business Example: Based on the company’s data (and sound integrity), we know factually that only 50 products were sold in the south east territory last quarter and the goal was 75. Also known is that the competition in that territory sold 25 similar products. Based on this data, a decision can be made to potentially increase territory marketing presence, research reasons competitive products were purchased, and re-exam projected sales forecasts.
Resource Utilization and Allocation.
Having the correct resources in the correct locations at the correct time working on the correct project is important. The adverse is detrimental and can give the competition an advantage.
Business Example: A decision to temporarily reallocate an inside sales representative from assisting in a territory that accomplished its sales goals early in the quarter to the south east territory could have meant achieving the sales goals and suppressing the competition.
Customer and Partner Satisfaction Management.
Essential to a company’s success is the satisfaction of its customers and partners. Whether it be surveys, on-site visits, etc., data needs to be routinely captured and analyzed to ensure customer expectations are being met or exceeded. Potential deficiencies or limitations in company products and services can be brought to light and resolved before the competition is aware.
Business Example: Not collecting satisfaction data on a larger customer in the south east territory meant not knowing about a small partner issue. This issue caused the customer to not purchase 30 additional products in the previous business quarter. If the correct individuals had known about this issue, a decision to swiftly resolve the partner problem would have led to the additional product purchase thus exceeding company territory sales goals.
As you can see, dynamic real-time data with solid integrity allows company decision makers to have a “pulse” on the company’s performance in the market and against the competition at any given time. Having accurate and reliable data to analyze into information for making important, quick or long-term, business decisions is a crucial tool.
Tips for Managing Your Company’s Data Integrity Effectively
It is one thing to understand what data is and why its integrity is important. It is another thing to effectively collect and manage it. At a high-level, companies typically collect data through various methods such as the following:
The Company Web site.
A common practice is collecting data from a company web site through page visits and mouse clicks, a contact us section, a request for quote (RFQ) section, a blog comments section (please feel free to leave a comment below), a product and services purchase (shopping cart) section, etc.
Enterprise Resource Planning (ERP) System.
An ERP system is business management software that integrates several facets of a company including product and project planning, manufacturing processes, material purchasing, inventory control, distribution, accounting, finance, human resources, sales and marketing, etc. Data is collected through manual or automated data entry.
Customer Relationship Management (CRM) System.
A CRM system is business management software that manages interactions and relationships with current customers, prospective customers, partners, etc. It can align sales, marketing, customer service and support. Data is collected through manual or automated data entry. Integration between an ERP and CRM systems is also common and can prevent data silos, redundant data and overall poor data integrity.
Back-end Database.
Behind the scenes will normally reside a database. Front-end applications such as web sites and ERP/CRM systems are “connected” to databases. Data entered in the front-end applications flow into and is stored in databases on the back-end. It is here where data is extracted and then analyzed through various means.
Most companies have this arrangement or a variation of this data collection methodology. With this understanding of data collection, below are a few tips for achieving and managing good data quality for your company:
Tip #1: Leadership.
It starts from the top down. Half the battle is won when your company’s leadership stresses the importance of company data and its integrity. When leadership and management understands this importance, strategic company goals and budgets are typically crafted with provisions fostering the implementation of a successful data methodology best suited for the company.
Tip #2: Governance.
Establish and put in place clear roles and responsibilities to ensure accountability for data quality. There should be “data owners” for various data segments. These owners are not Information Systems or Technology employees, but rather employees who know the data best. In other words, assign a human resources representative a role of governing employee data within the human resources module of the company’s ERP system.
Tip #3: Systems, Processes and Testing.
Front-end and back-end systems are the foundation for data capture and collection. On top of that foundation, processes are needed to secure data which is valid, relevant, accurate, reliable and complete. Processes consist of who, when, where, why, and how data is entered into systems. Creating process workflow diagrams showing the data input, output, and all the touches in-between is a “best practice” approach to test potential processes for accuracy and completeness before actual implementation within the front-end and back-end systems. These diagrams show how making a process change in one area can affect a data collection point in another area downstream in the data flow current.
Tip #4: Policies.
Develop and implement best practice policies and procedures to consistently check data. One such practice are data integrity reports that look for data inconsistencies in systems and processes. Such reports are a proactive approach to quickly bringing to surface a data or system process issue before it becomes a problem. A data integrity report example is “customer records that are missing a territory number.” Missing territory numbers could lead to sales commission, customer service, and billing issues. Discovering (through a data integrity report) and resolving this data issue before an improper billing transpires, proactively eliminates a potential customer satisfaction issue from occurring.
Tip #5: People, Skills and Training.
Having the correct people with the correct skills and training in the correct roles will significantly assist in effectively managing your company’s data integrity. People are ultimately the champions for good data quality. Typically, having accurate and reliable data makes jobs easier and employees more efficient, which leads to a self-interest to ensure good quality of data and improved company performance.