Many organizations strive to achieve business agility. The goal is to move beyond traditional business intelligence (BI) and enable more flexible design of BI access points and better delivery of information across the company. This type of agility can support an organization’s goal to tie in BI use with the overall strategic goals. This requires a BI platform that supports flexibility, access to information in an easy-to-digest manner when required, and a way to manage data effectively over time.
The common reason for evaluating Agile BI and self-service BI is that current BI initiatives are not meeting expectations, and businesses aren’t meeting their goals. Targets aren’t being met, value isn’t accurately defined, information isn’t getting into the hands of the right people, and data still resides in silos. All of these conditions lead to limited BI access – which, in turn, limits the amount of value that can be extricated from the system. The goal of agility is to take what exists and transform it into a toolset that users, irrespective of their business role, can use to explore and access information. Achieving this can sometimes require an overhaul of current BI investments or at the least a new outlook.
This article looked at some of the necessary requirements for achieving successful agility and self-service BI from the viewpoint of business decision makers. Much of the work involved requires strong IT involvement and taking into account technical requirements, while also providing a better experience for the user. The only way to develop this, however, is to merge both IT and business-oriented outlooks to ensure that all perspectives are represented.
The reality that organizations face is that a strong IT architecture is required to ensure continued data quality, centralized information access and agile delivery. With the plethora of self-service BI offerings, business units are starting to deploy solutions independently of IT, leading to self-service being managed at the departmental level. However, to guarantee continued access to valid information, organizations require a centralized, or governed, approach to self-service BI to ensure that data is being managed across the organization. This means making sure that data governance
practices are applied to any self-service initiative and that data is managed by IT. Front-end design and flexible delivery can be maintained at the end-user level, with data being managed by a centralized body and data steward input to ensure that data remains valid and reliable over time. This is where BI agility and self-service meet. Self-service refers to the end-user experience, while agility refers to platform development to ensure Agile BI support.
Enabling BI Agility and Platform Development
Achieving Agile BI requires certain architectural flexibility including right-time data access, flexible design and increased data visibility. Essentially, BI agility means developing the solutions, platforms and BI access points that ensure broader flexibility, have the ability to meet changing needs and support broader self-service and data discovery access points. Although the development of this type of framework falls outside the realm of business stakeholders, the reality is that for IT to get it right, there needs to be an understanding of the type of flexibility required. For instance, IT requires an understanding of the types of users, which can affect the levels of self-service access and the way data is delivered. This means that data consumers and data scientists will require different experiences in order to get the most out of the solution. At the same time, the platform should be developed to address this flexibility as opposed to having to build multiple solutions to fit the needs of a variety of users.
Data Access Points
Evaluating requirements is a precursor for the types of data required for analytics – not only how to access and interact with information, but also the complexities that exist between data sets and how they will be accessed within a centralized user interface. Agile BI requires information access points that expand beyond traditional BI. Big data is becoming essential to many data-related initiatives because of the newfound potential. This potential includes the ability to access and store a variety of unstructured and structured data that used to face limitations. Consequently, businesses are no longer limited by what they can analyze. They simply need to understand how the pieces fit together.
Fitting the pieces together can require great effort because the organization needs to understand how disparate data sources overlap and link to one another. This means looking at interrelated business processes, business rules or algorithms required, and the starting points for analytics. Because Agile BI and self-service access requires flexible interactions and not pre-defined analytics, data access points should be accessible enough to expand analytics and fact finding on the fly but secure enough to ensure that information is relevant, accurate and reliable. This represents the complexity of designing BI for agility because in the past this was not possible on a broad level.
Managing Information Assets Effectively
Managing information assets effectively is achieved is through proper management. Whether through a formalized governance program, or by assigning responsibility to specific stakeholders who will take ownership over the initiative, ensuring adequate management of information assets and making sure that data is governed will help lead to a successful Agile BI environment over time. Solutions can be set up successfully initially because they will meet the specific needs required. As more people start to interact with analytics and ask broader questions, the ability to manage agility becomes more of a challenge. The only way to support this growth is through governance and ensuring that self-service access points are maintained to enable users to interact with and manage information and analytics in the way that best suits them.
Organizations should develop a framework to understand which data entities are important to which departments, why they are important and how they relate to the organization’s performance more broadly. This level of knowledge can help businesses manage change over time and look at how to manage access to information effectively while also managing expectations.
Expanding BI to Achieve Greater Agility
Achieving Agile BI and self-service BI are not intuitive. Organizations require an understanding of technology, flexible interactions with analytics, data asset management over time and proper expectations. Although the promise of agility is great and possible within any organization with a little work, the reality is that to develop an effective solution means developing a strong platform that supports diverse data delivery and collection requirements. Click here
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