Business Intelligence Blog from arcplan

Best Practices in Budgeting, Planning and Forecasting Webinar Recording


In case you missed arcplan’s webinar on August 7th, Best Practices in Budgeting, Planning and Forecasting/CPM, here’s the recording to view at your convenience:


Note that the recording will stream as a WMV file.

This webinar is chock full of lessons learned from arcplan Edge deployments. Our Senior Vice President of Solutions Delivery, Dwight deVera, presents information you can use to guide your future CPM software implementations. As you’ll see, budgeting and planning project success comes down to a few factors: keeping expectations and scope in check, putting the right team in place, and selecting the ideal technology platform that gives all stakeholders what they need.

Leave us a comment if you have any questions!


Invest in Good Data Before Big Data


Big data is without a doubt 1 of the top 5 BI trends of 2012. The hype around big data has driven many companies to hoard massive amounts of structured and unstructured information in the hope of unearthing useful insight that will help them gain competitive advantage. Admittedly, there is significant value to be extracted from your company’s growing vault of data; however it is data quality – not necessarily quantity – that is your company’s biggest asset. So here are 3 reasons why you should devote more of your IT budget to data quality:

1) Because good data quality sets the stage for sound business decisions.
Sensible business decisions should be based on accurate, timely information coupled with the necessary analysis. Decision-makers need to be equipped with facts in order to plan strategically and stay ahead of the competition – and facts are entirely based on having correct data. Though it’s not as “sexy” as big data, mobile BI, or cloud, data quality should be the foundation of all of these other initiatives.

Admittedly, achieving data quality is tough. Gartner analyst Bill Hostmann says, “Regardless of big data, old data, new data, little data, probably the biggest challenge in BI is data quality.” It crosses department lines (both IT and business users must take responsibility), and processes that have multiple levels of responsibility often suffer from the “everyone and no one is responsible” conundrum. It’s also a complex process that requires laying out common definitions (what is a customer, what are our conventions for company names – Inc. or no Inc. – for example), performing an initial data cleanse, and then keeping things tidy through ongoing data monitoring, ETL, and other technologies.

But ensuring that your data is timely, accurate, consistent, and complete means users will trust the data, and ultimately, that’s the goal of the entire exercise if you see this first reason as the most important. Trusting the data means being able to trust the decisions that are based on the data. Clean up the data you have in place, then you can move on to a strategy that incorporates additional sources of big data.

2) Because you have to.

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Webinar: Best Practices in Budgeting, Planning & Forecasting/CPM Deployments – August 7, 2012


Join arcplan on Tuesday, August 7th @ 2pm Eastern for our free webinar on Best Practices in Budgeting, Planning & Forecasting/CPM Deployments, presented by our Senior Vice President for Solutions Delivery, Dwight deVera. This 60-minute webinar reviews a myriad of “know before you go” considerations for executives, finance teams, and planning professionals evaluating BP&F/CPM software.

We’ll discuss:

  •  How to translate your planning process into system design requirements
  • How to manage expectations and avoid scope creep
  • The “gotchas” and obstacles you may face during deployment and how to overcome them
  • Who should comprise your budgeting & planning team and their responsibilities
  • The elements of an ideal budgeting & planning system
  • And much more

We’ll also host a live Q&A at the end of the webinar.

You’ll come away from this presentation knowing everything it takes to achieve a successful technology deployment that enables you to dynamically adjust your plans on a monthly basis.

Click here to register!

Hope to see you there.


The Habits of Highly Effective Data Analysts


For decades, Stephen Covey’s book, The Seven Habits of Highly Effective People, has inspired many to be better leaders and managers by changing the way they work to abide by simple (yet profound) principles. With more than 20 million copies sold in 38 languages, Covey’s book has been used as a transformational tool for personal development in and out of the corporate world.

As a tribute to Mr. Covey, who passed away this month, I’d like to explain how successful data analysts may be following his advice without even knowing it.

Be Proactive.
Covey believed that proactive leaders take responsibility for their actions and focus efforts on their circle of influence. Being proactive is particularly important for analysts supporting decision makers who make strategic and operational decisions for the company, since the analyst is often their most trusted advisor. Analysts need to be aggressive in extracting crucial business information and unearthing insight beyond what is immediately obvious in the data. Their job is focused on culling trends and patterns from data, then using that information to make recommendations to those who have the authority to enact changes and solve problems. While they’re often mired in data from the past, their focus is on proactively predicting future outcomes.

Begin with the end in mind.
This habit urges us to envision our desired goal before starting the hard work of making it a reality. Analysts do not simply deliver reports to decision makers – they answer business questions with data and provide recommendations on how to proceed based on what-if scenarios and statistical analysis. If the quandary they’re presented with is how to maximize sales efforts at their company, they would investigate the data, perhaps finding that the company doesn’t have enough opportunities at the top of the sales funnel; therefore, there will never be enough opportunities at the bottom of the funnel, i.e. closed deals. Starting with the end in mind – a revenue goal – they would drill into the data to cull insights, then work with their team to recommend a plan of action.

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Mobile BI Strategy Checklist: Part III


Over the last week, I’ve been discussing the items you should consider before jumping head-first into mobile business intelligence. You can find Part I here and Part II here. Today I’ll evaluate the final 2 items that might be the most important yet – architecture and security.

7. Mobile architecture plan
This discussion is a bit technical, but it’s important to understand the basics. If you’re approaching mobile BI from the business side, you’ll be able to intelligently discuss this topic with IT. I recommend a VPN (virtual private network) architecture to our mobile BI customers. It’s the easiest to set up and it supports the growing BYOD (bring your own device) movement. Most devices already include VPN capability without the need to install software to make it work. VPN solutions involve sanctioned and managed connections to the corporate network. All traffic over the VPN is encrypted, so even if your users are on a notoriously insecure network like airport wifi, the corporate data they’re looking at on their mobile devices is secure.

Here is a typical mobile BI VPN client configuration:
mobile BI VPN architecture
From a reliability and performance perspective, these deployments are identical to traditional desktop/laptop clients connecting to the company network. They would require users to login to the VPN, but that extra step is worth it to protect access to corporate data.

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