How To Pick The Right Analytics Project For Right Now

Perhaps the biggest concern for anybody managing an organisation's BI analytics projects is deciding which problem to focus on in the coming months. There's always a plethora of good candidates, and the list of options can seem overwhelming. However, the implementation of a proven selection process is relatively simple, and it can be reduced into a sequence of steps that are easy to follow.

Find the root of your most difficult difficulties

It's best to begin with identifying the bi ggest issues. You may be falling short of revenue targets, your manufacturing operations are operating inefficiently, or you're unable to find the right resources at a fair price. Most likely, you already have a good idea of the issues and do not need to spend too much time to create an inventory. It's not important to analyze the list too much at this point, but it is essential that you write everything down.

It is possible to inquire if the problem includes an analytical element.

You now have a list of problems. It is possible to filter your list to determine which ones include an analytics component. This article explains how to answer this issue. The fact is there are some problems where analytics isn't a factor. If the parent company of your business is making a change to its policy that's impacting you negatively such as, say you're probably not able to determine if using analytics to resolve those issues. The goal is to narrow the list of issues to ones that analytics could assist. It is possible to think of issues like forecasting, market and customer segmentation, management of campaigns, as well as decision support. Is there a suggestion? If you have a spreadsheet or an information system that is that is involved in the issue the chances are that analytics have an important role in the solution.

Determine where analytics can be able to

You must determine at which stage of the business process the use of analytics can influence decisions quality. For instance, imagine that a fashion retailer has put together an order of winter jackets for teenage girls. What number of times could you find data intersecting or decisions factors? It is likely to involve historical transactions, loyalty cards information, weather data, data on national demographics (there is more teenage girls in Manukau than Tauranga to name a few). If you haven't already now, it's probably an ideal time to talk with professionals in analytics and insights (in-house or outside) and establish three things:

1. Which of these decisions can be improved with the application of analytics?

2. What's the most likely value of improving those decisions by using analytics?

3. How much would it cost to carry out the analysis required?

Consider your options and make a final decision following a thorough evaluation

It's getting close. You've identified big issues that require BI analysis and pinpointed the intersection of information, decision-making and operational processes. The benefits that can be realized by making these decisions better and also the expense to do so have been quantified. It's now time to perform the maths. Set aside those projects when the return is likely to be minimal or mediocre. It's better to deal with the situation.

Now, all you're left with now are your potential high-value analytical projects. The final filter is? When you have a number of options but are not sure where to begin make sure you prioritize the ones that are most closely with your organization's mission.