Market conditions change at the drop of the hat, and enterprises have to make the best possible decisions at the right time, based on relevant information from business intelligence solutions. However, according to a Gartner report from a few years ago, between 70 and 80 percent of corporate BI projects fail. Patrick Meehan, research director in Gartner’s CIO Research group believes that most of these projects fail due to poor communication between the management and the IT department. The repercussions of a failed business intelligence implementation are often painful, and may include lower staff productivity, morale and in some cases, lost revenue. Ineffective change management lies in the process of preparing the workers affected by change, rather than in planning the implementation.
You might be wondering, why change management is so important. Well, some strategic business events such as mergers involve major changes over three or more years; others, like restructuring have to be implemented in less than a year. In the case of business intelligence, major changes might need to happen within a few weeks, or in some extreme cases, few days. All of these changes will eventually lead to either achieving or failing to achieve business results. Successful business intelligence implementation brings greater profitability, which is a true indicator of success. Of course, miscommunication is not the only reason why so many projects fail, there are numerous challenges every enterprise has to face in order to implement the technology successfully and reap the benefits of business intelligence. Enterprises have to understand and address these four challenges for BI success.
1. Cross-Organizational Cooperation
You have to realize that business has to be driven by the customers and the market, and not by manufacturing plants and product managers. It is also crucial to correct any customer problems before the customer even realizes the problem existed, because enterprises have a better chance to experience consumer loyalty if consumers can pay when their problem is solved and not when the product is shipped. Where business intelligence is concerned, collaboration is not limited to departments within the enterprise, it requires a combination of knowledge about the customers, the competition, market conditions, products and employees at all levels. To implement BI successfully, an enterprise must develop and maintain a cross-organizational cooperative culture, in which everyone works toward the strategic vision.
2. Dedicated Business Representation
In most cases, the primary objective of BI projects is technical rather than business-orientated; this mostly happens because BI projects are often run by IT managers with limited business knowledge. IT managers tend not involve business communities, so it is not surprising that so many projects fail. As a rule of thumb, 20% of key business people use BI apps 80% of the time, so it is crucial to identify key representatives at the beginning of the project and keep them motivated until the job is done. A successful BI team should involve stakeholders from different areas – business executives help make decisions, and have to be solicited for determining the project’s direction; customers can identify the final goals of the BI system and the IT department provides technical expertise and analyzes present BI-related requests.
3. Business Analysis and Data Regulation
You probably already know that Bi projects are data-intensive, and that “data out” is just as important as “data in”, so it is vital that the source data be inspected and analyzed. In most projects, business analysis problems are related to source data, which is scattered around the enterprise in separate data stores and in a number of different formats. There are two main issues with this. The first one is identifying data needs. Most analysts have challenges when it comes to identifying business issues related to BI app objectives. The second one is data merge and regulation. Perhaps the biggest challenge faced by every BI projects is its team’s ability to comprehend the scope and the importance of making the required data available for knowledge workers. That data consists of fragments in different internal frameworks, and it must be merged into a common data warehouse, which is not a simple task.
4. Impact of Inaccurate Data
It is imperative to identify which data is important and determine how clean it is, because inaccurate data can cost an enterprise millions. Therefore, any dirty data must be recognized and isolated, and a data-cleansing plan must be developed. Even the best BI plan is practically worthless if driven by dirty data. Therefore, it is important that every project employ a few knowledgeable analysts who can ensure the quality of source data. In addition, BI software such as the Panorama Necto can help any enterprise to collect, analyze and store data, and share the information with the team.
The Difference Between Change and Project Management
Keep in mind that change management and project management are two different things. When enterprises decide to implement changes, detailed plans put the framework in place to make those changes a success. While change and project management work in parallel, they still have many points of intersection. Change managers mostly look at which people will be affected by the changes, project managers focus on aspects like timelines, tasks and technology. With any change, you cannot focus only on the management aspects of the change; you also have to think about the workers.
In this day and age, you cannot simply leave the technology to the IT department. In business intelligence, this is especially challenging with the added complexity of increased enterprise involvement, and unlike other business IT applications, where the enterprise and IT partner up, in BI the enterprise owns many components and work streams. Basically, in the world of business intelligence – technology is everyone’s job. So you have to pay particular attention to several ways in which change managers differ from change managers, and perhaps most importantly – BI projects are iterative, while BI change management is constant and ongoing.
Nate Vickery is a business technology expert and a futurist mostly engaged in finding and implementation of the latest technology trends into SMB and startups management and marketing processes. Nate is also the editor-in-chief at business oriented blog- Bizzmarkblog.com.
Subscribe to Data Informed for the latest information and news on big data and analytics for the enterprise.
Source: Data Informed