Today data is the new fuel for businesses and a well-crafted data strategy is important for realizing the full potential of business data. With the continues evolution of data management & data visualization ecosystems, the importance of a data strategy becomes a top priority of growing businesses.

A well-defined and robust data strategy can help businesses improve decision making, operations, innovations and complete well in market.As per report from Forbes, Industrial organizations collect mountains of data on everything from asset performance to maintenance needs, but many lack a plan for how to organize that data or maximize its value. In fact, 60% to 73% of data in an organization is never successfully used for any strategic purpose, according to Forrester. As a result, companies miss key opportunities to streamline operations and grow their business. A great data strategy should:

1. Eleminate data silos

2. Bolster data-storage strategy

3. Implement strong security & access control

Common Data Strategy Challenges

As businesses start their digital transformation projects, here are some of the commonly faced challenges:

1. Data Silos

Enterprise data comes from various sources in different formats.This data is either collected from external (e.g. Google, USPS, WHO) or internal (Operational systems) systems. This data is often stored on local machines of the business divisions (stakeholders) and processed as per their specific requirements. As a result, it lacks enterprise adaptability due to absence of ‘single source of truth’, data fragmentation, data quality issues.

2. Lack of Centralization

Data fragmentation makes it difficult to achieve enterprise-wide view of the real time business ecosystem. Decentralization of the data ignores the enterprise level ‘single source of truth’ (view) required for better decision making.

3. Lack of Security & Access Control

A poor access control mechanism causes outsiders to gain unauthorized access to organizational data. Outsider breach can be attributed directly to a lack of security & proper access control mechanism.

Aligning Data Strategy with Business

Well designed data assessments & due diligence can help identify inefficient and outdated data management processes that limits the capability of the businesses to make informed decisions. Many times (within departments) data management processes run in isolated manner. That means at every department, the data is extracted, modeled, transformed, aggregated, calculated, and presented to business as per the speficic department requirement. During this process, many efforts are duplicated with inconsistent results & little to no reuse. A well planned data strategy can help balance each of below four business areas.

Summary

Data driven leaders like Chief Data Officers (CDOs), should showcase the importance of data strategy to business teams & spearhead the efforts to develop their enterprise data strategy for buidling a strong data foundation. Businesses should conduct necessary due-diligence & assessments of the current data management landscape. Most times, external, unbiased teams play a better role in these types of assessments that result in presenting the current state, proposed (future) state & the road-map. In addition to the common data strategy challenges & business alignment goals, the businesses should proactively focus on auditing the existing data, standardizing data, centralizing the data, security and access controls.

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Preparo Analytics empowers data driven leaders with data and analytics solutions to make businesses stable, better, & competitive. The company enables  data driven leaders with data driven strategy, data discovery, assessments & roadmaps.

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