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How To Achieve Business Intelligent IT Migration

IT Strategy local_offer

Administrivia. That was the word that did it for me. It's not that I have a great dislike of the buzzword bingo that proliferates the management meetings of today, it's more that these highly paid people are being so distracted with the day to day need to blind the managerial opposition and report on some (any) progress that they are not concentrating on what they are really being paid to do, which is to make decisions. And what makes a great decision making team apart from great people? The facts, that's what. Just imagine, sitting in a meeting reviewing dynamic, actionable information based on the latest real-time data available. That's what we attempted to create when we formed Juriba; a company that truly believed in transparency of business intelligence data to make informed, actionable decisions and available 24/7 for IT transformation projects and Evergreen asset management. Of course, this means a significant shift in changing culture from reactive reporting to working dynamically, and removing the continuous churn of cottage industry reports that are so much the face of many IT project management meetings of today.

IT departments today have a multitude of data from which to make their decisions. The challenge is not so much in collecting that data, it is in how we use it, and how to drive a much more agile analysis culture. A few years ago, we sat through meetings reviewing project progress as each team reviewed its spreadsheet status. By the time that the questions have been answered on what was happening, how it might impact the project, and what was being done to rectify it, the organization had often moved on and changed it's footprint and processes. The review loses relevancy - it's already out of date and people have moved on. What's really needed is to manage the transformation in real-time, and ideally to predict what could happen before it occurs. These are the traits that will differentiate the IT project managers of tomorrow from those stuck in the past, churning out their monthly reports for an audience that is working in the here and now.

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But exactly how can we manage the environment in a more pro-active model and deliver an organization towards dynamic, accessible business intelligence to support the ever changing IT landscape? These are some of the main considerations that we reviewed when we designed our Dashworks software.

Understand the business requirements

BI means something different to everyone that wants to use it. Therefore, when designing a new system, and gathering a mass of requirements, you might find huge organizational engagement, but an implementation timeline of years. Distilling what is really important to multiple levels versus what one individual thinks might help them is a complicated task and where many BI solutions fail. Get someone that has worked their way through the organization in multiple roles, understands the needs of the staff and managers, and can judge the merits of each requirement based on actual value. This enables you to identify the quick wins whilst keeping an eye on the strategic goal for the system.

Stakeholder Buy In

You would be amazed at how many people will design a fantastic BI reporting system, but completely miss the senior sponsorship requirement. So why is this so important in BI implementations? Well, most BI is focused around faster delivery of information, better visualization, and ultimately, the reduction of roles due to the increased efficiency and better decision making that this delivers. Now, who will be the main dissenters in the mix? Probably the people whose job it has been to produce this information manually, their management chain, and potentially the owners of the data itself, worried about what the transparency will highlight. So, make sure they are involved, get the senior level backing, especially about the bottom line returns, and make sure they drive it down the organization, and finally involve the people that currently 'work' the data. They may be negative initially, but you'll often find a progressive type or two that can really help you deliver a better system.


Raw data is boring and often too complicated to understand. However, information can be really interesting if it's obvious what you are looking at and the data is correctly tied back to the base for mining. So what makes a good BI system? Well, firstly, make it graphical. KISS or keep it simple, stupid is as applicable today as it has always been - only a niche set of resource are planning to look at reams of statistics. Employ someone to properly 'skin' your system, use big bold colours for red/amber/green status, use graphing tools to present information and historical data, and most of all, make the interface dynamic. Allow your users to click anywhere, link the data points, aggregate data for summary levels and make it flashy. Much as we always like to believe that content is king, we also love a 'wow' factor, so give the users what they want.  Pretty graphs and colours still work for some!

Data Quality

Probably the most difficult thing to get right in a BI system is the quality of the data that you render out. Simply speaking, a single, negative comment from a CEO where incorrect data has been displayed can have a massive impact on the success of your implementation. So, check and treble check that the numbers add up, test thoroughly that any drill down views are working correctly, and most importantly, ensure that when you are pulling from multiple data sources, that corruption or failure of those data extracts do not ruin the integrity of your current data. 


The latest generations are used to having a multitude of information at their fingertips instantaneously. No point having the best BI system in the world if your pages take minutes to load. They'll get bored and soon switch to either doing it themselves quicker, or investigating a different source. So speed is of the essence. Make certain that your technology can deliver pages in no more than 5 seconds, preferably less than one second is optimal. Of course, with major technology advancements in Microsoft SQL, analysis services and other database engines, this is becoming easier and easier to achieve, and again, is critical to the success of your implementation.


BI need not be a holy grail of data management. In fact, I would argue that everyone that manipulates a spreadsheet with more than one data source is actually applying business intelligence to their role. Having implemented multiple BI solutions for everything from application workflow to problem ticket management, the biggest lesson I've learnt is that people roughly know what they want, they just find it hard to start from a blank page. However, many people are great at seeing something and improving on it. Therefore, get the original information views up there quickly. It will drive innovation and more often than not, give you directions you would never have thought about before.

Juriba's Dashworks product is designed to achieve all of the above in the ever changing end-user IT environment. We use business intelligence to drive organisational behaviour, reduce expense associated with both business as usual and investment projects and improve operating efficiency. Our customers are saving millions of dollars/pounds annually by getting there faster and through the ability to truly see their world.

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