We use cookies, including third-party cookies from Google to serve personalized ads through AdSense, to operate this site and understand how it is used. By continuing to browse, you accept this use. See our Privacy Policy and Terms of Use for details, including how to opt out of personalized advertising.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    What Kind of Problem-Solving Distinguishes Data Analysts From Software Engineers -- AI-generated illustration
    What Kind of Problem-Solving Distinguishes Data Analysts From Software Engineers
    7 Min Read
    chatgpt image jul 21, 2026, 04 34 30 pm
    4 Core Benefits of Predictive Maintenance after Vibration Analysis
    10 Min Read
    How Does Data Mining Boost Customer Satisfaction in Logistics? Harnessing Analytics for Results -- AI-generated illustration
    How Does Data Mining Boost Customer Satisfaction in Logistics? Harnessing Analytics for Results
    11 Min Read
    chatgpt image jul 13, 2026, 04 23 45 pm
    How Data Analytics Helps Companies Improve User Engagement
    19 Min Read
    chatgpt image jul 13, 2026, 03 59 46 pm
    How Data Analytics Improves Multi-Location Search Strategies
    10 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: Is There One “Right” Strategy to Implement Business Intelligence?
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Business Intelligence > Decision Management > Is There One “Right” Strategy to Implement Business Intelligence?
AnalyticsBusiness IntelligenceDecision ManagementPredictive Analytics

Is There One “Right” Strategy to Implement Business Intelligence?

Ray Major
Ray Major
7 Min Read
Is There One "Right" Strategy to Implement Business Intelligence?
Illustration generated with FLUX.2 [klein 4B] via Cloudflare Workers AI.
SHARE

Implementing a successful Business Intelligence strategy in the Food and Beverage Industry is simple — just stick to a few key rules

This past week, I spent a considerable amount of time with some of our food and beverage supply chain clients who are in the early stages of implementing a Business Intelligence Strategy. What I learned was interesting and reminded me of an old Hungarian saying my mom used to use – “Ahány ház, annyi szokás.” Knowing that many of you probably don’t read Hungarian, in English this translates to “There are as many customs as there are houses.”

So what does this have to do with BI strategies you ask? Well it seems from all my conversations that “there are as many BI implementation strategies as there are companies.” That got me thinking, is there one “right” strategy to implement BI? I don’t really think so. Just as each household is unique, and has its own set of customs, so is each business.

Each business, has its own set of needs and challenges. For instance, one client faces pressure from a growing number of store types catering to specific consumer needs, such as supercenters, membership clubs, and convenience stores. Another is looking for opportunities to take advantage of the Consumer demand for more food options that meet a variety of needs, including health, taste and convenience, such as the “Gluten Free” fad. And yet another is trying to wrap its head around public policy and consumer sentiment is that is driving product traceability and fueling the demand for private label, organic foods and product freshness.

More Read

First Look: Provenir Big Data Listening and Engagement Platform
First Look: Provenir Big Data Listening and Engagement Platform
Interactive Intelligence Doubles Down on Cloud Computing
PAW: Predictive modeling and today’s growing data challenges
Wil Wheaton is Just Some Guy, You Know?
New Trends in BI, Analytics and Social Media

Because these challenges are so diverse, and for the most part these challenges are on top of all the other Business Intelligence work that a company has to do, each requires a unique BI implementation strategy. With that said, there are some commonalities that I think make life a little easier for everyone involved in rolling out a BI solution.

My advice: involve the end user; think big, but start small.

So let’s involve the user. There is so much awesomeness that can be gained from a well-executed BI solution. For example, one of our customers put together a “Traceability Taskforce” to create a forum where input from all involved could be taken into account. Like planning a group vacation, everyone has great ideas, experiences from the past, and most importantly, expectations of what the vacation will be like. Hearing what the people who will ultimately be impacted have to say, and involving them early is a key critical success factor in any BI implementation. Allowing the users to have input early in the process creates buy-in and ultimately lays the foundation for a successful BI rollout.

The drawback of involving the user community in the definition of the BI system is that you will end up with more (waaay more) ideas than can be implemented in an initial roll out. This, however, can be leveraged into the “think big” part. Allowing input from various departments, and involving end users and working with a BI expert creates a big picture view of how BI could ultimately benefit the organization. This will be different for every company, because each company has its own set of challenges and personalities. Vet and prioritize these requirements, and identify a few key problems that can be solved relatively simply.

This is where you start small. Roll something out and allow users to get used to the concept of using data and metrics to drive their behavior. Not everyone will be a convert immediately, so watch for resistance and address it as part of your strategy. Each business will have its own pace at which it can adopt and absorb new technologies and ways of thinking.

Push, but not too hard, or you will get resistance. Orchestrate some quick wins with some simple analytics. You’ve seen the sign by the bathroom in many big box hardware stores “This establishment accident free for (fill in the blank) days.” This, by golly, is a simple KPI metric used to measure site safety. Just posting this helps change employee behavior.

Once you start to realize the benefits from the initial analytics, you can start to roll out the more complex ones; metrics that will be used for strategic or long term planning purposes.

One idea might be to replace the reliance on spreadsheets, which by their nature contain errors and provide different answers to the same question, with a tool that allows everyone to see the same data at the same time (i.e., “one version of the truth.”)

To avoid disappointment, plan on a BI strategy full roll out to take not just a few months, but more in the range of 1-2 years. Provide new capabilities in stages, or phases. This allows your users to acclimate to the new way of doing business, and provide feedback on a contained functionality set. Massive implementations tend to require a tremendous amount of staff effort, and often create more problems than they solve. A phased approach can also help with business continuity and keep everything running smoothly.

Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

Flat editorial illustration: A tech-editorial depiction of contextual re-identification risk in linked unstructured support recor
Stripping the Names Isn’t Enough: De-Identifying Unstructured Data
Exclusive Unstructured Data
Flat editorial illustration: The article connects practical management of local data, memory and software environments with direc
How Data Professionals Optimize Devices for AI and ML Projects
Artificial Intelligence Data Science Exclusive Machine Learning
Flat editorial illustration: The article connects verified lease abstraction at signing to accurate property charges and faster m
AI Lease Abstraction and Month-End Close Speed-Up Checklist
Artificial Intelligence Exclusive
Flat editorial illustration: The article explains that file-system choice determines whether Windows, macOS, and Linux can read o
Understanding File System Compatibility Across Windows, macOS, and Linux
Cloud Computing Exclusive

Stay Connected

1.2KFollowersLike
33.7KFollowersFollow
222FollowersPin

You Might also Like

How to Speak Like a Data Scientist
AnalyticsData Visualization

How to Speak Like a Data Scientist

5 Min Read
Big Data and the Internet of Things: A Powerful Combination
Business Intelligence

Big Data and the Internet of Things: A Powerful Combination

6 Min Read
The Road to Success with Big Data: A Closer Look at Expectations vs. Reality
AnalyticsBig DataHadoopMapReduceSQLUnstructured Data

The Road to Success with Big Data: A Closer Look at Expectations vs. Reality

5 Min Read
AI Is Empowering Everyone to Become Their Own Branding Expert
Artificial IntelligenceBusiness IntelligenceExclusive

AI Is Empowering Everyone to Become Their Own Branding Expert

6 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

From Bolts to Bots: How AI Is Fortifying the Automotive Industry
From Bolts to Bots: How AI Is Fortifying the Automotive Industry
Artificial Intelligence
The Art of Conversation: Enhancing Chatbots with Advanced AI Prompts
The Art of Conversation: Enhancing Chatbots with Advanced AI Prompts
Chatbots

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-26 SmartData Collective. All Rights Reserved.
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?