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Enabling effective change.

Lee Ann Healy
30th January 2017

Business Intelligence

Business Intelligence software (BI) is becoming an essential tool for most businesses. Being able to analyse what’s happening in your business and base decisions on accurate, trustworthy data is key to being able to survive and thrive, particularly in the current climate.

For manufacturing businesses there are many benefits of BI.  Since they are operating in a very competitive environment with not a lot of wriggle room – business intelligence can be a key element to gaining competitive advantage.  BI used to really only be an option for the big manufacturing firms.  Going back to the earlier years of my career and the BI projects I worked on implementing the likes of Cognos and Business Objects – invariably they cost a fortune and took a very long time to implement.   In fact, the projects often petered out without ever having been implemented properly as the business got fed up of it sucking up budget, time and resource for very little return.  My memories of BI projects in the bad old days is that they were usually a nightmare – it almost put me off BI for life!

However, these days there are many more Business Intelligence options out there that come at a much lower cost, are much faster and easier to implement and can deliver real business benefits.  It’s now a much more valid option for the small and medium sized manufacturing companies.  We’ve been implementing BI systems such as Tableau and Qlik for some of our manufacturing customers over the last few years and it’s restored my faith in BI.

In some cases, it’s meant that they’ve got much more value out of their underlying ERP and business systems.  So rather than having to replace these legacy systems we’ve put a BI solution over the top of them which provides the integration and collation required to give one view across the business.  So many businesses, particularly in manufacturing, still have disparate systems and silos of information.  The ERP, the WMS, the Shop Floor control systems etc etc.  Which inevitably leads to an inordinate amount of time moving data around, manually collating dat, and generally a lot of jiggery pokery leading to mis-information and untrusted data.

In all cases, not only has it resulted in improved analysis and reporting which drives better decision making but also improved business processes and better use of the underlying business systems.  The way we approach a Business Intelligence project is that the business data needs to be right.  If the business processes and system set up isn’t right then the data it produces won’t be right.    We always take the approach that we need to go back to the root of the data.  Sense check that the data is accurate and has meaning – it’s so dangerous to go down the path of producing nice, colourful dashboards and flashy reports that then become the basis of key decisions.  But if you actually trace the data back to the roots properly – it’s flawed.  That can turn in to really costly mistakes.  Our advice is to always take the time up front to get this bit right – the temptation is to just get the key reports or analysis out as quickly as possible, just get to the answer.  But it needs to be the right answer.  So in our experience, the time spent doing it correctly up front the first time will be much less in the long run to fix and unravel poor data flows and BI solutions further down the line.

The Business Intelligence technology itself these days is so impressive and you can get fantastic results.  We’ve noticed that on the last couple of Tableau implementations we’ve done – our customers absolutely love it, across the whole organisation from the exec team to the operators.  Because it’s very user friendly and can produce very clear and concise outputs that are tailored to different needs.  But to take advantage of the technology you need to get the basics right ie get the underlying processes right, which in turn means the data is right.  That gives you a robust platform to build out from.  I think I’ve probably laboured the point enough – get the data right!


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