In Business Intelligence

In Business Intelligence, Sound Governance Drives Adoption And Success Via Enablement

In Business Intelligence, Sound Governance Drives Adoption And Success Via Enablement

What does the title mean?

An April 2016 report from Forbes Insights strongly suggests that the most successful business intelligence (BI) programs feature processes and solutions that place analysis and decision-making solutions in the hands of local business units and functions: so-called ‘distributed’ or ‘self-service’ BI. Specifically, Analytical Enablement: How Leaders Harness Distributed Business Intelligence to Drive Breakthrough Results, found that a majority of respondents (53%) say their overall BI programs are delivering significant benefits.

But what also stood out was that the number of companies reporting significant benefits rose to 87% among the group identified as “leaders”. Moreover, a key attribute of this group is that leaders tend to exhibit significantly higher degrees of self-service within their BI programs.

So the question became: How are best-of-breed BI programs able to balance self-service against the need for data governance? And what we learned in follow-on research, our October 2016 report Breakthrough Business Intelligence, is that those companies achieving the greatest value from their BI programs were doing so through a nuanced and sophisticated blend of governance and distributed BI.

Read Also:
Governed Insight: The Power of MDM and Analytics

Nothing drives adoption and usage like success. So the more success end users experience with BI the faster and more deeply it will spread throughout the organization. But the research found a range of issues that continue to plague the realization of BI’s full potential. Frequently-cited problems include instances of inconsistent data, multiple versions of the truth and inconsistent formulas/definitions and limited adoption across the enterprise.

The common thread? All can be addressed via better governance. And indeed, our research further reveals that companies seem to understand this too and are taking steps to address problems such as those just mentioned. For example, 83% are doing more to manage data access at the departmental level, while 81% are assigning data access by role.

Being able to control who is able to see what data and when is actually a means to enabling broader general access to data. This is an idea that absolutely resonates with Carolin Borchert, Worldwide Business Systems Analyst, Data Warehouse & Analytics, at Germany’s MTS Sensor Technologies GmbH & Co.

Read Also:
Machine Learning Templates with SQL Server 2016 R Services

 



Data Innovation Summit 2017

30
Mar
2017
Data Innovation Summit 2017

30% off with code 7wData

Read Also:
The best of big data NoSQL: MongoDB, Amazon, and DataStax top Forrester list

Big Data Innovation Summit London

30
Mar
2017
Big Data Innovation Summit London

$200 off with code DATA200

Read Also:
Bottlenose Takes on the Data Scientist Shortage

Enterprise Data World 2017

2
Apr
2017
Enterprise Data World 2017

$200 off with code 7WDATA

Read Also:
8 Reasons Why Analytics / Machine Learning Models Fail To Get Deployed

Data Visualisation Summit San Francisco

19
Apr
2017
Data Visualisation Summit San Francisco

$200 off with code DATA200

Read Also:
8 Reasons Why Analytics / Machine Learning Models Fail To Get Deployed

Chief Analytics Officer Europe

25
Apr
2017
Chief Analytics Officer Europe

15% off with code 7WDCAO17

Read Also:
Internet of Things Transforms Business for Supply Chain Industry

Leave a Reply

Your email address will not be published. Required fields are marked *