A strong partnership between IT and business is the most important, and often overlooked, component to successfully managing critical business data. Undertaking business intelligence, data quality or an enterprise data management project without full cooperation and collaboration between IT and the business is a formula for frustration. 
Critical business data consists of data elements that materially affect the company’s processes, results, reporting, legal obligations, intellectual property and reporting. This includes data that influences financial reports, regulatory compliance and key business decisions such as pricing, credit risk and supplier management.
Identifying and defining critical business data requires a strong alliance between business and IT. Both organizations must agree on how data is created, updated, controlled, reported, deleted and archived. Many data projects fail because the partnership to manage these changes was never in place or was not strong enough to endure a lengthy project. 
So how do you create and maintain an effective partnership between IT and business? Here are four steps that we’ve found successful:

  1. Know your partner. 
  2. Develop a relationship.
  3. Define roles and responsibilities.
  4. Establish open, regular communication channels.

Know Your Partner


Forging a successful partnership begins with assessing your partner’s biases and experiences in data management. There are usually three segments of potential partners:

  1. Friends get it immediately. They understand the value of data management and of having an effective IT and business partnership. They are considered friends of data.
  2. Converts don’t understand data issues when they’re first explained and really don’t see why they should. They may have responsibilities that depend on data management, but may not know that they need to support these efforts. They can be converted, however, and energized to care about data. Once converted, they can be your most passionate supporters.
  3. Naysayers don’t get it and never will. These individuals truly don’t understand why investments in time and resources are necessary, and they are usually very vocal in their opposition. They espouse that data management is the responsibility of “another group.” 
  4. Beware. This group is also very fond of generalizing data issues and pointing incessantly to data quality problem. The difference between this group and the converts is that this group is rarely interested in becoming part of the solution.

Once segmented, the partnership approach starts with these strategies: 
For those friends who get it, make them your evangelists. Call on them often to share success stories, herald their successes in your presentations, and recognize them as heroes. Look for these individuals throughout the organization. 
For those who don’t get it, but may eventually, convert begin a structured and systematic education program. Develop either a broad company approach or tailor one for specific organizations. Here are few suggestions:

  • Teach this group about the benefits of data management. 
  • Instruct them on the hows and whys of good data quality processes. 
  • Use their processes as examples. 
  • Make the lessons short and specific to their jobs. 
  • Make sure that lessons are convenient to take and easily understood. 
  • Use your evangelists to help you with this instruction. It gives them visibility and supports your cause. 

Once this group has completed training, they become part of the converted. Engage your new converts in some data activity or project immediately after their data training sessions. This gives them the chance to use their new skills and helps install them as permanent converts.
For the naysayers, minimize their effect on the organization. As long as their skepticism is contained and managed, you can continue to sell the concepts of data management to management. Pinpoint these individuals early. But be wary; they do not always initially look, talk or act like people who are distracters. When these individuals populate the executive ranks, you have a unique challenge. Here you must work actively to surround them with positive friends and converts. Be prepared to counter negativity about maintaining data with hard facts.  If you are going to forge a successful relationship between business and IT, you need to ensure that your partner comes from either the friend or convert categories.

Develop a Relationship


Oil and water don’t mix, but given a vigorous shake they become great salad dressing. Like oil and water, IT and business need something to bring them together. That’s usually a joint objective. To be successful, both must appreciate the different roles each plays in the company and in data management. Here are a few methods that help the partners learn from each other:

  • Attend each other’s staff meetings and strategy meetings. This gives you information and insight into the challenges faced by your partner and how they manage them.
  • Participate in “a day in the life” sessions. Nothing strengthens the partnership more than walking a day or an hour in each others’ shoes. 
  • Spend time understanding the details of a project or issue. Pick a challenge area that your partner has and spend time truly understanding all the issues around it. Avoid the tendency to solve the problem. Your goal is to understand what he or she is facing. 
  • Show public appreciation of the other’s team. Building camaraderie between business and IT teams begins with the leaders. If the leaders appreciate each other openly and often, the teams will follow.
  • Jointly report to management on the progress of the team. Progress reports usually happen through separate channels. If you can’t report on your joint progress to a combination of your management teams, at least agree between yourselves what is to be presented – both content and context. 

Define Roles and Responsibilities 


Clearly defining the roles and responsibilities each group plays in data management is easier written down than actually accomplished. The overall function of data management, whether in IT or the business, has three major roles: business/operations, technology and executives.
Let’s start with the role the business and operation teams play in data management:  

  • Define business critical data, required data versus optional data (logical level). The responsibility of the business owner is to ensure not only that the right data is represented in the data sources but also to exclude superfluous data. Start with the data that you must have in order to accomplish the task for which the system is designed. 
  • Define business requirements for quality, timeliness and accuracy. These may be different for each process in your business. For example, it may be absolutely critical that the system that manages service for your customers is updated hourly, whereas the data for your personnel system may require only a weekly update. 
  • Approve business rules for transforming data. If data has to be transformed or edited to ensure the desired quality level is achieved, the transformation rules for those decisions are approved by both the business and operations.
  • Hold business suppliers/partners accountable for good data. It is the responsibility of the business to establish the quality guidelines for data suppliers and to ensure that their data is accurate. If possible, include these requirements into contracts and hold the supplier accountable when metrics are not achieved. 
  • Approve the conceptual/logical data model. The business and operations teams approve the relationships and entities of the logical data model.
  • Ensure business processes are designed for guarantying high quality data for all uses. This is a very important, often overlooked, responsibility of the business owners. The business’ and operation’s manual processes and the employees that create, update or delete data should also be designed for high quality data management. 

Technology roles complement the deliverables and roles of the business and operations teams: 

  • Define critical requirements for the data at the physical level. Once the business team has defined the required logical data elements, the IT teams define the physical elements such as physical name, size, format and attributes.
  • Identify the best source or sources for the data. Make sure that you have agreement from the business as to what “best” really means. Because data elements may exist in various databases across the company, especially if a master database exists, the IT team determines the best source for the data elements based on the quality requirements defined by the business and operation teams.
  • Hire skilled data architects, modelers, database administrators, data quality specialists. Data projects need skilled data technologists, and the IT team is responsible for ensuring the right level of IT skill is present and applied.
  • Define the data architecture and the standards to be applied to the data. The specific IT rules, such as naming conventions, data modeling standards, database design and development standards are defined by the IT team. 
  • Select the data tools. The IT team selects the data technology tool that best meets the needs of the business and operations requirements. This selection process may require collaboration among the teams if business processes are to be changed. For example, the selection of the vendor for customer data cleaning should be a joint effort.
  • Implement and define the physical model for the data. Once the logical data model is defined collaboratively between the business function and IT, the physical data modelers define the next level.

Executives of both the business and IT have special roles to play in joint projects:

  • Set realistic expectations and measure. Establishing a measurement for the return on your investments in data projects is helpful to ensuring that you meet your objectives.
  • Set the example for data management behavior. An executive that tells his or her team that all data projects will be handled centrally then starts his own skunkworks project is a bigger liability to data management than the executive who doesn’t support any data projects. Walking the talk is a requirement.
  • Commit to a multiyear program and set metrics to ensure quarterly or yearly return on investment. Most large, multiyear data programs can go off track quickly if they are not managed with urgency. Establishing long-term goals with short-term measurements is the solution.
  • Establish and actively participate in data governance forums. Establishing the data governance forum is the first task; attending the forums and providing guidance is the mark of an involved executive. Conversely, forums become ineffective if business, IT and operations management are not present and actively involved.
  • Think and act strategically. Once a collaborative, multiyear data management program is agreed to between business, IT and operations, then tactical, quick actions can be taken as assumptions and business change yet still working toward the goal.
  • Appoint business leader(s) for data management. Select these individuals carefully, ensuring they are as passionate about solving the problem as they are about articulating it. 
  • Resolve cross-division conflicts. Conflicts across the business, operations and technology teams come up in any data management program. Executives demonstrate their commitment by resolving these conflicts quickly before team cooperation erodes.

Open Regular Communications Channels


Ongoing communication at all levels, but especially between the key leaders, is essential to successful collaboration. The willingness to constantly give and accept feedback must be at the heart of the communication process. Here are some other tips for enhancing this communications challenge:

  • Dream the same dream. Make sure that each of you understands the goals and dreams of the other organization.
  • Mitigate the middleman. In many companies, business functions have a middleman group that interfaces to IT. They write requirements, perform preliminary testing and report status on projects. While there are advantages to this approach, it often leads to confusion and a weakening of the partnership between IT and the business. You can do without them.
  • Trust the cooks to cook. The more you know about the other organizations’ challenges, work processes and culture, the greater the tendency to respond on their behalf. Avoid this at all costs. If each organization sticks to what they do best and trusts the other to do the same, the result is better.

With some thought and attention to the relationship between IT and business, your data projects will successfully contribute to your organization’s objectives.

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