Demystifying predictive analytics: design your analysis

This is part 3 in a series designed to show your organization how to create a customer-centric organization with predictive analytics. Get started by analyzing the status quo and evaluating your infrastructure.

Saken Kulkarni

Saken Kulkarni

Before entering into a career in Big Data and analytics, I was interested in becoming a Foreign Service Officer. I was fascinated by ancient history, international development, and War Games. As a college student, I remember that the most interesting classes in the course registrar required some less-than-intriguing prerequisite courses. I tried to get around taking these classes, to no avail. But looking back, it’s a good thing that my university enforced these prerequisite courses. Developing a well-rounded knowledge base enables you to think contextually and critically to drive new ideas forward. Read more of this post

Making Tableau an essential part of your BI stack

Ronak Shah

Ronak Shah

The BI landscape is evolving. Over the last 10 years, analysts and line-of-business users have gained access to an overwhelming amount of information and new tools.

It’s no secret that technology’s changing every day, and with it, a new set of expectations for how we do our jobs. So how do we leverage the BI tools we know and continue to provide meaningful insights while keeping pace with the latest technologies? For starters, we need to understand the limitations of traditional reporting, and next, figure out how to best structure and empower our IT teams and analysts with new tools—like Tableau. Read more of this post

Demystifying predictive analytics: evaluate your infrastructure

Saken Kulkarni

Saken Kulkarni

Technology’s changing by the minute, and so is your customer’s behavior. How do you find out where your customers are and how they’re making purchase decisions, and then swiftly react when that all changes? Customer-centric, predictive analytics are an important piece of the solution, and a key theme at NRF’s 2014 Big Show (and what this blog series is all about). A couple weeks ago, I talked about how to start building a customer-centric organization by analyzing the status quo. The next step is evaluating your infrastructure to lay a solid foundation for your analytics program. Read more of this post

Microsoft BI helps look into the past, present, and future

Dan Montgomery_headshot

Dan Montgomery

A nationally known shopping mall owner/operator partnered with Slalom Consulting to design, develop, execute, and continue to evolve a state of the art, centralized Enterprise Data Warehouse (EDW) and reporting/analytics platform. After transitioning from a legacy platform to a Microsoft based EDW, the client was able to leverage the entire suite of reporting/analysis tools in the Microsoft BI stack, including direct integration with the MS Office suite and SharePoint. These tools have given Slalom Consulting the ability to deliver unique, insight-driven projects that focus on not only providing a historical view of data, but also an ongoing look into the future of the company’s financials.  Read more of this post

Demystifying predictive analytics: analyze the status quo

Saken Kulkarni

Saken Kulkarni

A few weeks ago, I wrote about how retailers can leverage analytics to get a more complete picture of their ultra-connected customers. I also presented a five-step road map pointing the way there.

Over the next few weeks, I’ll outline these steps in greater detail. In the process, I hope to demystify advanced analytics and help C-suite executives successfully implement a data-driven culture within their organizations. Read more of this post

Catering to the king: leveraging advanced analytics in a customer-centric economy

Saken Kulkarni

Saken Kulkarni

Fifteen years ago, sellers ruled the retail landscape, freely proposing the price for goods and services dictated by market or, very often, themselves. This “take it or leave it” attitude prevailed because customers had few resources to counter prices and shop around.

Today, the environment has changed. A customer looking to buy golf clubs for a weekend getaway can comparison shop on eBay or Amazon, and then post a comment on Facebook asking for opinions. The customer can then browse reviews of local driving ranges on Yelp to try out his or her new purchase. The proliferation of social media, ecommerce platforms, and mobile usage has created an ultra-educated class of consumers and has allowed the customer to have ultimate control of his or her purchasing decisions. The retail landscape has dramatically changed—the customer is now king. Read more of this post

Developing a Successful Analytics Strategy

Carrie is the Practice Area Lead for Information Management at Slalom Consulting. With nearly 20 years of experience delivering business intelligence solutions, Carrie now specializes in Advanced Analytics. Utilizing quantitative approaches to uncover actionable insights based on consumer behaviors, attitudes, perceptions and attribute, Carrie has serve as a trusted advisor to help clients assess their current analytic and data infrastructure challenges and then implement the architecture, processes, and organizational requirements needed to address those business challenges.

Carrie is the Practice Area Lead for Information Management at Slalom Consulting, specializing in Advanced Analytics. With nearly 20 years of experience delivering BI solutions, Carrie helps clients leverage quantitative and qualitative results to meaningfully drive their businesses.

As a major part of our work within the Advanced Analytics Practice at Slalom Consulting, we guide our clients toward the right balance of activities, information, and insights that allows the experience and intuition of the decision-makers to be guided by appropriate information and quantitative analysis. This balance sits at the intersection of finance, operations, sales, and marketing, and encompasses the broad field of advanced analytics, which is currently getting an immense amount of attention in the business press. With this new awareness comes much hype and confusion about how to effectively execute an analytics strategy. From our work with hundreds of clients across many industries, we have found six essential considerations for developing a successful analytics strategy.

Establish Common Definitions to Deliver Consistent Information

While the finance team specializes in categorizing and defining information consistently, marketing (and to a lesser extent, operations), often uses less robust definitions. Metrics such as “awareness” for advertising or “footfall” for store operations are not necessarily defined or captured in the same way in each instance. Bringing together a business’s core groups to adopt a common set of metrics, agree upon how to govern the collection, and determine how it is used will help ensure smoother cross-team communication.

Business activities around promotion, marketing, competitive impact, and operational events are not necessarily captured in the same fashion as general ledgers or sales transactions. However, to have a consistent view of internal and external information, these data points must be captured with a degree of care similar to that used with key enterprise assets.

Apply Business Knowledge to the Process

Insights are most valuable when they leverage the experience of the team along with a broader set of trusted internal and external findings. The most successful teams will include representation from finance, operations, sales, and marketing, all communicating in a common language and with shared understanding. Knowing how data is collected and having specific business rules in place for analyzing that data is critical to understanding statistical insights.

Advanced analytics are only useful for making solid business decisions when all three legs of the stool are in place: data (internal and external), business and domain knowledge, and statistical models.

Select and Capture the Appropriate Metrics

In today’s global enterprise, there is no shortage of financial, operational, sales, and marketing metrics. However, we see wide variation in the discipline and use of this metrics. A study by Currim and Mintz at the University of California Irvine shows that an appropriate use of combined financial, operational, and marketing metrics can be a significant predictor of business performance.

The study indicates that higher-performing companies use a two-to-one balance of financial to marketing metrics, whereas lower-performing companies overweigh their financial metrics. Interestingly, there is a wide variance in the use of metrics by type of marketing activities. Most firms, regardless of their performance quartile, measure pricing or promotion performance. However, companies in the lower ranges of performance typically don’t measure social media or public relations, while top-quartile performers measured at least four key metrics in those areas

Keep It Simple and Experiment Often

When trying to be more analytical, companies often fall into the trap of adding unnecessary complexity. This is often driven by the natural risk avoidance inherent in large organizations, coupled with a reliance on quantitative analysts tasked with finding one “right” answer. As with most things in life, business decisions can seldom be delivered by one complex model that returns the perfect response. The most successful decision-making models often operate with the smallest number of factors possible to arrive at a reasonable answer.

Promote a Culture of Sharing and Storytelling

Insights are not very useful unless shared with the entire decision-making team. It’s natural to sometimes hold on to knowledge that may give one a perceived internal advantage, but this short-term thinking does not allow an organization to grow analytically. Encourage sharing within your organization by using stories. Create a story on the front end to generate hypotheses, and on the back end to help craft the final message to your audience. In the middle, use research methods, data, and statistics to quantify, evaluate, and modify the thinking.

Rewarding team members who not only create insights by leveraging new data sources or models, but also then sharing those insights with others in the organization will help foster teamwork and morale. Team thinking is essential to not only capitalize on the collective wisdom of the group, but also to allow your best analysts to move on to new areas of exploration.

Take a Measured Approach

The evolution of the decision-making process must be undertaken at an appropriate pace. Trying to displace too many decisions with quantitative or scientific models too quickly will invariably backfire. Organizations must have the time to allow analysts and managers to learn from the newly available information and to supplement their current processes before undertaking new ones.

In working with our clients, we help them keep these considerations in mind as they craft their analytics strategy. Striking the right balance here results in a strategy that maximizes the organization’s return on their analytics investment.

We would like to hear your thoughts regarding this approach to building an analytics strategy.  What do you think is the most important consideration?

Carrie Steyer is a member of Slalom’s Information Management Thought Leadership Committee. For more information, email the team at

A BI Recipe for Success with Surface RT

SurfaceThe Surface with Windows RT devices have been roaming the streets for several weeks now. More than a few companies are trying to get ahead of how this type of device is going to be incorporated into their IT landscape, and Business Intelligence departments are often at the front of the line. We have put together a little recipe to enable interesting and useful Business Intelligence delivered via the Surface RT.

Mobile devices are primarily consumption devices. Windows 8 changes the equation, but it does not change the fact that when people are on the go—without large monitors, traditional keyboards, and mice—they are going to skew more toward consumption than creation.

Clearly mobile devices are becoming more and more prevalent. There is a fantastic tie-in here to business intelligence. The information provided through BI does not add any value if it is not consumed. Gartner predicts by 2013 a third of all BI functionality will be consumed on mobile devices. I am not sure what point in 2013 they expect to pass that threshold, but happy new year!

I am excited for the reinforcements in mobility that Windows 8 naturally brings to the Microsoft BI stack. However, as a fan of PowerPivot I was a tad sobered to see this blog post by Analysis Services guru Kasper de Jonge. PowerPivot is not available on Windows RT. And for that matter neither is Silverlight and, therefore, Power View. Kasper does remind us that Excel on Windows RT will still create pivot tables and can connect to a Business Intelligence Sematic Model (BISM) service. That is useful for some lightweight analysis within the Excel App with an online data source.

However, if you are connected, which you would need to be anyway to take advantage of a BISM multidimensional cube or tabular model data source, why not take it a step further and let the cloud do as much work for your consumers as possible? That is what we have done with the following recipe.

A few simple, out-of-box ingredients:

  • One fresh Surface with Windows RT (for the consumer)

The Surface offers fantastic new hardware. Discussion and reviews are bountiful, so we will not go into too much detail here.

  • A handful of SharePoint Online 2013 Enterprise with Excel Services (for the provider)

This is the secret ingredient. Using SharePoint Online makes this a fully fledged cloud-based solution which plays nicely with those mobile devices, and their users, that refuse to sit still. Users  even have the option to expose a pivot table field list and adjust the report on the fly.

Excel Services in SharePoint 2013 include some exciting new features, like Quick Explore, which empowers drill-down and enables real ad hoc data interrogation for power and regular users. To keep the data up to date, we’ve seen success leveraging a script to refresh workbooks hosted with SharePoint Online.

  • A dash of Excel 2013, or in a pinch Excel 2010 with PowerPivot (for the report author)

Authoring reports in Excel, with its strength in data source compatibility, allows all of the data modeling and authoring to be done in the world’s most popular analysis tool. Report authors need not be developers and the cost of creating new reports drops to new lows. Through the use of finger-friendly slicers, charts, and pivot tables you can easily provide users with an experience that feels nothing like looking at a spreadsheet.

Surface BI SharePoint Online Demo Small

This is a Surface RT screenshot, straight from Internet Explorer. From portal to report: long press for the pivot table field list and quick explore drill-down right in the graph or table.

We have found that mixing these ingredients creates a dish that delivers some hearty BI morsels.

To be fair, a browser-based delivery mechanism is not unique to the Surface RT. In fact, quite the opposite is true. Providing users with the scrumptious data and visuals they crave through the browser is about as cross platform and cross form-factor as you can get. This is—mostly—a good thing. The only reason to qualify here is that you’ll need to consider the variety of mobile and desktop devices (as well as their screen sizes and aspect ratios) that your users will leverage to access reports. If you are able to target a specific device, or use creativity to steer users to a specific version of a report based on a specific device, then make your reports shine for that device. However, we recommend balancing your time between crafting perfectly placed pixels and creating a generic report that offers rich insights on a variety of devices.

What makes the Surface RT useful as a BI delivery tool, particularly in this recipe, is really Excel Services on SharePoint 2013. The half-second press and hold gives you touch access to Quick Explore drill-downs along with the power to edit the pivot via the “Show Field List” option. With SharePoint Online supporting Excel Services, you can easily create a 100% cloud-based BI solution. Like all recipes there are modifications which you can make to better suit your needs. For example, if you need to support larger data sets (more than a few million rows) or are looking to leverage some of the more advanced features in SharePoint 2013, then running the on-premises version of SharePoint server will allow you to scale that processing capability and feature set as needed. The screenshots below are based on a data connection to Salesforce CRM (but could be Microsoft Dynamics or almost anything).

Bon appétit!

Slalom Intelligence

Side-by-side comparison of the Surface RT and iPad.

Slalom Consulting PowerPivot Architect Barbara Raney was a co-contributor to this post. These authors are members of Slalom’s Information Management Thought Leadership Committee. For more information, email the team at

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