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Why smart organisations move from data gathering to actionable data

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Data is a main artery of modern organisations.  In a volatile and rapidly changing environment, it is those organisations that can assess their progress against their goals and change course quickly that are likely to succeed.  To track progress and make quality decisions, you need high quality information and data.


Shelf of papers and inbox on wooden desk
Analysis Paralysis?!

I recently saw an interesting case study and video on Phil Simon’s blog.  The case study relates to a US based pizza chain “Papa Gino’s” and describes how the senior management team recognised the importance of data and implemented a business analytic solution.  They made significant progress – being able to much better understand their business, the success of their marketing campaigns, and their customers.  Now, I’ve never worked in a pizza restaurant, so why was I so interested you may ask?  The case study may have been related to pizzas, but the underlying learning points could equally apply to a tech company, insurance providers, car manufacturers or any other business of just about any size.  I’m yet to come across a business that doesn’t create, use or rely on some kind of data!


One comment that particularly resonated with me in the embedded video was the move from “data gathering to actionable data”.  This is an extremely important observation… I’m sure we’ve all seen and worked with organisations that spend hundreds of day’s effort each year collecting and collating data, and then simply don’t have the resource to trawl through and interpret it, and certainly don’t have the resource to take action on it.  Having data is useful, but being able to take action based on it is far more important.   Having too much incomprehensible data can be a real barrier to decision making, leading to a classic case of “analysis paralysis”.


Some organisations create a mini-industry in data collection and management reporting, which might involve extracting data manually from multiple sources manually, mapping it and then synthesising it into a summary report.  This works well for small teams with defined data-sets, but as organisations grow and the data becomes more complex, it becomes more difficult to manage manually and there’s greater room for error.  Growing and mid-size companies are particularly vulnerable to the pain: It can become increasingly difficult to interpret complex data, and the more frequently you’re translating/transcribing/copying/coding/importing the data, the greater the risk that the end-report could contain inadvertent inaccuracies (I’m sure we’ve all had that “ooohh no!” moment when working on complex spreadsheets – that moment when we realise that we weren’t interpreting or using the data quite the way we thought we were!).  In a worst case scenario, when we’re dealing with enterprise-wide data, these inadvertent inaccuracies could mean the CEO makes a critical decision based on data that’s not correct.  A scary thought!


Having actionable data often involves the move towards clear visibility of a consolidated set of key performance indicators that are based on trustworthy data, alongside the ability to “drill down” into further detail when necessary.


As with any business problem, it’s important to assess the business need and choose a solution that is fit for purpose.  However the days when business analytics solutions are only of use to large multinationals have long gone.  They are equally useful to mid-size organisations who really want to understand their businesses and their customers. Defining the data that’s important to you, understanding how that data is created assigning a “data owner” are all important steps in working out the right solution for you.  Spending time up front defining the business needs and understanding the data will pay dividends in the long run – whatever type of solution you choose!


In summary: Data collection is important.  Having succinct and actionable data (and taking action on it) is where you’ll reap the rewards!



What are your experiences of collating and using organisational data? I’d love to hear your views – please go ahead and add a comment below!


This post was written as part of the IBM for Midsize Business program, which provides midsize businesses with the tools, expertise and solutions they need to become engines of a smarter planet.

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