When undertaking a large project, there is always a high probability of failure and resulting consequences can usually be catastrophic for organizations. In the case of BI projects, the failure rate approaches a daunting 80% (Gartner).
Whether through exceeding the budget, missing deadlines, or more importantly, failing to achieve the objectives that the project was designed for, failure looms around the corner in every undertaking. Thus, great care must be taken at the planning stage to ensure readiness for future success.
Today, we outline several critical initial steps organizations should take to avoid failure before embarking on business intelligence and analytics journey. This information applies to postal, parcel and logistics organizations, as well as any large enterprise in any domain that wants to improve decision support. Also included are strategies to optimize business processes through BI and predictive analytics.
Align your initiative around existing business problems
The project should not be a solution to a non-existent problem. Take great care to understand the concrete problems within the business that need solving and create your analytics strategy around them.
The direction is set from the top down. A massive undertaking like a BI or data analytics implementation requires organization-wide buy-in, alignment with the corporate vision for success, backing by executive management, and endorsement and acceptance by all verticals and technical professionals managing your current information technology domain.
Understand Your Existing IT Landscape
Planning to initiate a BI and analytics project without taking into consideration the organization’s current information technology landscape is a risky maneuver. It is, after all, the existing infrastructure and environment that will be integrated with the BI stack to produce actionable insights for achieving business goals later down the road.
Cloud, big data, analytics, mobile, video, social, and self-service channels must be taken into account. In addition, planners must identify needs for integration of data, hardware, algorithms, speech recognition, natural language processing, translation between languages, images, objects, sentiments, and keywords. Analysis of audio/video and unstructured data, through to understanding human intelligence are all key aspects of auditing existing business and technical needs as we review the IT landscape and future needs.
Furthermore, a future overhaul of the technology landscape to suit a hastily purchased BI platform will always be very expensive. To minimize this risk, organizations need to consider the nature and number of applications and data sources, the current data-state, hardware sizing and infrastructure, anticipated data growth, governance policies and other aspects related to the IT framework.
Additionally, it goes without saying that the organization must assign appropriate roles to competent resources with support from technology partners.
Identify Roles and Select a Competent Partner
The traditional technical teams in a typical business will need support from an experienced BI partner, a vendor that has the industry knowledge and a track record of implementing end-to-end BI projects. Similarly, the partner will need support from the IT team to tackle multiple issues that they are certain to encounter during the implementation. A trusting relationship between these two teams can do wonders for your initiative and achieve business objectives seamlessly. Therefore, business units must ensure the involvement of the IT department when selecting the BI partner.
Business needs are paramount; therefore, it is imperative that organizations carefully assign roles to in-house resources and appoint a BI partner that can deliver a single source of truth to business functions within agreed timelines.
Remember, 80% of BI projects fail, and one of the reasons is a lack of due diligence before selecting a BI platform. Team up with the BI partner to assess and develop a road map that saves you from the pitfalls.
Develop a BI Roadmap
Now that the roles are identified and a BI partner is on board, the next step is to develop a roadmap that defines a phased approach to implementing a BI project. Developed after an assessment that includes your current technology landscape and business needs, a typical BI roadmap highlights the readiness of fundamental elements and recommends changes that are essential for a successful BI implementation. This is usually a one to three months’ activity depending on the organization’s size and current state. Finally, the roadmap recommends one or several BI platforms to choose from. The right platform is the one that suits your budget, integrates with your current IT landscape seamlessly and caters to long term business needs.
Larger organizations need to focus on developing a BI and analytics ecosystem where one tool or platform may not be enough.
Following are the visionaries, leaders, and challengers within the BI space which fulfill basic needs for decision support:
Leaders: Information Builders, Oracle, Microstrategy, Microsoft, IBM, QlikTech, SAS, SAP
Challengers: Tableau, Tibco Software
Niche Players: LogiXML, Actuate, Prognoz, Panorama Software, Salient Management Company, Board International, Targit, Arcplan, Alterix, Pentaho, and Jaspersoft
Following are the visionaries, leaders, and challengers within the Algorithm-driven BI, AI, and Analytics space, representing the next step in the evolution of strategy optimization:
Visionaries: DAtaiku, Domino data labs, H2O ai, Microsoft
Leaders: Quest, Alteryx, Angoss, Mathworks
Challengers: SAS, IBM, KNIME, RapidMiner
Niche Players: Teradata, SAP, Fico
Stay Tuned for future content including:
How to Select the Right BI Tools
Algorithm-driven Business Strategy Optimization.
How to Create the Right Analytics Ecosystem
How to Select the Right AI Toolset