2017 was a busy and tumultuous year for the beverage alcohol industry, especially those who were affected by the wildfires in California. This year also brought many company mergers and consolidations, continuing an ongoing trend in the industry.
What’s clear as we head into 2018 is that technology and analytics are becoming even more important than ever, and it’s important for the beverage alcohol industry to adopt tools that will lead to improved efficiency, increased productivity, and more revenue. With that in mind (and since the holidays are on our minds), I created a holiday wish list for better business intelligence and analytics in the beverage alcohol industry. (more…)
Here at Dimensional Insight, we realize that the holiday season means something a little different to everyone. Some might look at December as a time for holiday festivities involving excessive or not enough gift giving, fun and/or awkward dinners with in-laws, and more holiday music than any sane person can possibly tolerate.
However, if you are working in the beverage alcohol industry, the holiday season is the busiest time of the year, as it’s a major determinant of whether or not your year is going to be a success. With OND (October-November-December) representing on average 60% or more of your sales, it is an important revenue driver for everyone in the industry. Accordingly, your company will pull out all the stops to capitalize on the opportunities unique to the 4th quarter of the year, with pricing, promotions, and increased marketing and sales activities being foremost among revenue maximization strategies.
While everyone starts their business intelligence (BI) implementations with the noblest of intentions, these implementations can often turn into hair-raising experiences worthy of a horror movie. It’s great that you now have an analytics tool to help you make better business decisions, but how in the world do you implement this big hairy beast of a project? It’s a frightening prospect, and can often be fraught with delays and data issues. In fact, there are a wide variety of estimates as to the percentage of BI projects that are considered failures. Some statistics say 50% while others say 70% to 80%. Any way you slice it, that’s downright terrifying. Eek!
Yes, business intelligence can be scary, but before you scream that blood-curdling scream that I know is just dying to come out, sit down and take a breath. You CAN do this. You just need to know the demons you’re up against, and how you can beat them. (And no, it does not involve garlic or stakes through the heart. Come on, now.) (more…)
Imagine walking into a car dealership and having a sales representative offer you a Ford for $25,000. In deciding whether to accept the offer, you would be faced with a considerable list of additional questions. What model? What year? New or pre-owned? What horsepower engine? What basic amenities? The list goes on and on. Most sane people wouldn’t make a decision to buy the car without obtaining answers for all (or at least most) of the follow-up questions.
Why is it then that many business people are willing to make decisions after only asking one question?
I’ll admit: my house needs a good spring cleaning. It’s been 10 years since we’ve moved in, and there’s lots of stuff shoved away that has sat untouched for pretty much that whole period of time. There are papers that have been misfiled or not filed at all, a bunch of out-of-date technology sitting around (anyone want a rabbit ear TV?) and some knick-knacks that should have been tossed out ages ago.
Chances are you have a lot of the same problems with your data. It’s old and taking up unnecessary space, or isn’t being used correctly, or is dated and just plain wrong. And here’s the kicker: bad data is not just a nuisance, but it’s expensive, costing the average business millions of dollars every year.
The statistics are sobering: As we have discussed in the past, one of the most surprising takeaways from the Gartner business intelligence Magic Quadrant is that by 2016, 90% of self-service business intelligence (BI) initiatives will lack the data governance required to prevent inconsistencies capable of negatively impacting an organization. Unfortunately, many businesses today are implementing BI without a game plan, and they are just hoping and praying that it all goes well.
Don’t cross your fingers and hope that luck strikes. A good business intelligence implementation is the result of careful planning and diligent execution. In fact, research by Aberdeen Group shows the top strategies of organizations that are successful in their data discovery efforts. In honor of St. Patrick’s Day, we’ve created this business intelligence infographic with 3 tips based on those success strategies to show how you can cut through the blarney and get your pot of BI gold at the end of the rainbow – no luck required. (more…)
Business intelligence (BI) projects are notorious for being heartbreakers. All too often, BI buyers dive in head first without thinking about the goals they are trying to accomplish. Or they purchase a BI platform that doesn’t have the functionality they require. Of course, that leads to failure.
For Valentine’s Day, we created an infographic on 3 ways you can avoid BI heartbreak and how you can find true love when it comes to business intelligence.
2014 was a busy year for those of us who work in healthcare technology with hospitals having to manage changes to the meaningful use program, coming under continuing pressure to lower costs and readmissions while improving patient care and outcomes, and figuring out how to deal with an onslaught of data generated by an ever-increasing number of apps and devices.
As 2014 draws to a close, it’s time to reassess what has worked and what hasn’t worked in healthcare over the last year, and renew ourselves for 2015. (more…)
Healthcare organizations must handle a growing list of expectations (EHR implementation, meaningful use compliance, lower readmissions, etc.) To meet these expectations, providers must fully master the landslide of electronic healthcare data, both structured and unstructured, that is housed across multiple departments. It’s not an easy task.
Analytics (in theory) promises to help address these challenges, providing the insight to help reduce operational costs, optimize IT systems and help clinicians make the best decisions for their patients. Unfortunately, as we all know, “in theory” and “in practice” are two different things.