Those of us with grey hairs gained in the IT industry will have less than fond memories of requesting reports, developing a spec and scope, and then handing them over to the IT department, only to wait… and wait… and wait. Fortunately, there’s a better way. Combining the latest BI toolsets with agile methodologies can deliver a fast impact to the business in terms of profitability and return on investment.
Agile enables incremental projects. We typically work with clients’ business and IT teams to define the scope collectively, and then we work in 10-day sprints on an identified issue – far removed from the old days of ‘waterfall’ projects where you might be waiting six months.
The big difference with today’s agile, self service tools is that they don’t require coding and scripting. They’re drag and drop, which puts the data into hands of people who need to work with it and ask questions of it.
All along the way, you see the results it’s an iterative build. It’s modular so you can explore, interrogate, visualise and conceptualise. It’s designed to fail early, so if you don’t like it, you can quickly stop it and start again in a different direction. Does that sound familiar? I liken it to Lego; the building blocks – that is, the underlying data – remain the same but, like a child who builds a house and then breaks it to use some of the same pieces to make a car, what you choose to make is limited only to your imagination.
One trap to avoid is falling into old habits: don’t replicate reports in the format you’ve always had. Reports by their nature are historical and look back. The key difference with analytics is that it allows you to see patterns and possibilities – what’s happening in the business right now, and what could potentially happen in the future.
“One trap to avoid is falling into old habits: don’t replicate reports in the format you’ve always had. Reports by their nature are historical and look back”
Analytics presents data in a meaningful and insightful way that empowers business users to make decisions that will have a direct impact on cash flow profitability now, rather than waiting for the end of the month or quarter. Here’s an example: analytics identified €1 million worth of dead stock at a retailer, who was able to take this knowledge and release cash back to the business.
Any large business has hidden data that often obscures a myriad of issues. By using analytics to shine a light on previously unseen information, businesses are able to make better decisions faster. Once discovered, this information can also drive a decision to create a policy to ensure such stock overruns don’t happen again. It could even end up being a KPI or a risk area for the management team to monitor.
We estimate that many projects start seeing a return on investment after 12-13 months, and much of that is driven by labour cost savings. Because the work involved in building reports is now with the business owner, and it takes far less time to see results, staff productivity increases as they’re released to perform other important functions in the business. We recently completed a project for a large financial institution that traditionally handled reports at month end by taking data from its internal SAP system. This took a senior manager four days to work on. Our work to automate the process reduced this time to one hour. Or, about as long as it takes a child to build a Lego house.
Peter McParland is CEO of Perception Data Consulting
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