30 Days – 30 Great Customer Stories

It seems like only a couple of days ago that I posted my blog announcing my 30 days of customer success! But alas, time flies, and today I posted the final story through my @jamesafisher Twitter account.

As promised, I’ve listed all 30 customer success tweets here for you in one place.  I hope you enjoyed reading them.

All that’s left is for me to thank you all for your support over the course of 2013, and to wish you and your families a very happy holiday season and all the best for an amazing new year in 2014.

  1. ATB Financial: Driving Customer Focused #BI
  2. MISC Berhad: Responds Quickly to Keep its Customers Moving
  3. How TeliaSonera Is Improving Decision Making from Any Location, Anytime
  4. Vodafone Germany Puts #predictiveanalytics on the Fast Track
  5. Cooper Industries Simplifies Trade Compliance Throughout the Enterprise
  6. NBC Universal Upgrades #planning and #forecasting for Real-Time Analysis
  7. How VELUX Is Using #BI To Optimize Business Performance
  8. Wolters Kluwer Drives Customer Retention with #predictiveanalytics
  9. How City of Boston Is Using #EPM Solutions To Engage with Residents
  10. Old World Industries Improves Data Analysis, Planning, and Forecasting
  11. Deloitte Seeks Visibility into Profitability, Talent, and Internal IT Projects
  12. Royal Shakespeare Company Puts Advanced Analytics Centre Stage
  13. Zappos Drives Visibility into Reporting Supply Chain and Reduces Time to Close
  14. Danone Leverages #EPM To Use Less Fuel, Lower Emissions and CO2 Footprint
  15. SRAM Drives Faster, More Flexible Reporting with Greater Visibility into Operations
  16. Virgin Media Uses Predictive Analytics To Drive Customer Retention
  17. Villanova University: Empowering the Non-Profit Sector with #SAPLumira
  18. Sigma Aldrich Empower Users with Enterprise Self Services and Visualization
  19. Sharp Standardizes GRC Processes to Free Time for Innovative Product Delivery
  20. Barclays Moves into the Predictive Modelling Fast Lane
  21. SA Health Optimizes Patient Flows with New Dashboards
  22. South East Water: Tapping a Wellspring of New Business Insight
  23. Titan Cement Company: Setting New Standards for Financial Excellence
  24. Sears Boosts Productivity with Predictive Analytics
  25. Why Medtronic Chose SAP #HANA and BW to Stay Competitive
  26. Ace Hardware Using #BPC To Budget Plan and Forecast More Efficiently
  27. Lenovo Uses SAP HANA To Support Real-time Decision Making and Improve Time To Market
  28. Levis-Strauss Streamlines and Tightens Business Processes To Cut Costs
  29. US Cellular Optimizes the Customer Lifecycle with Predictive Analytics
  30. Unipart Group Gains Visibility into the Company’s Supply Chain

Recap: Week 1 of #30Customers

First week and first of my 5 #30Customers have been shared.  Here’s all 5 in case you missed them. More next week via Twitter @jamesafisher… Have a good weekend.

No.1 – ATB Financial: Driving Customer focused #BI  bit.ly/19dfpyb

No.2 – MISC Berhad: Responds quick to keep its customers moving  bit.ly/1aOreBk

No.3 – How TeliaSonera is improving decision making from any location, anytime  bit.ly/1aOrgsJ

No.4 – Vodafone Germany puts #predictiveanalytics on the fast rack bit.ly/19dfMbR

No.5 – Cooper Industries simplifies trade compliance througout the enterprise bit.ly/1aOrm3P

30 Days of Customer Success

I’ve been on the road for what feels like the last five weeks and have hardly been home at the weekend. So when I got back to London from California this weekend and walked through our local shopping area, I was somewhat surprised to see that Christmas had arrived.

The shops and streets are sporting festive decorations, and all the bars and restaurants are advertising their Christmas menus.  I’m a fan of the holidays – but not in November.

So in an attempt to defer Christmas (for now) and get through to mid December without having to see Santa Claus: The Movie seven times, I’ve decided a distraction is in order.

So please join me in celebrating my very own countdown to the holidays – 30 days of customer success!

‘Tis the Season for #30Customers

Each working day over the next six weeks I’m going to post a link on Twitter to a new customer story. These stories all inspire and show how enterprise business intelligence, agile visualization, and advanced predictive analytics are being used by our customers to drive collective insight.

At the end, I’ll summarize them all here in a blog.

Follow @jamesafisher and the hashtag #30Customers and not only will you not miss a single one, but by the time we’re done it will just about be time for the 12 days of Christmas!

Are You Ready to Unleash the Power of Collective Insight?

When I started this blog a few months back I had the best of intentions however in recent weeks I’ve been a little remiss in terms of sharing my thoughts with you. I offer no excuse other than that we’ve been very busy, which is the trap many probably fall into when launching a new blog. So in order to get myself back on track, I looked back at what I’d shared to see where I should go next.

It became clear to me that a trend had started to develop in terms of the things that were catching my eye. I shared my thoughts on the use case for Big Data, I talked about the need for education in analytics, and tried to convince you that I was the model of a typical analytics user. While diverse in nature, I see all of these pointing (perhaps not unsurprisingly) to a new way of thinking about analytics. I don’t mean in terms of the latest trends associated with “Big Data” or  the coolest visualization capability, but actually thinking about the role analytics should play in our work and personal lives.

This got me thinking a bit more: how do we really use analytics today? And, how can we ensure that future generations use analytics in a way that makes sense? The fact is, examining these blogs has led me to the conclusion that we are missing a huge opportunity.

Big Dark Data

As my Big Data blog implied, I’ve been pretty critical of broad, undefined use cases for Big Data and have grown increasingly tired of the numerous “V’s” associated with it. The issue is not that “Big Data” exists, but that we’re failing to take advantage of the opportunity.  Frankly, just like we spend too much time on e-mail and not enough time actually talking to each other, we spend too much time looking at data in silos and not collectively talking about its meaning.

The problem with this is that while many great inventions have come from a single person, the majority of things we all take for granted today have evolved over time with the input of many.  If we’re truly to exploit the opportunity of Big Data, the connected world which feeds it, and subsequently find the use cases that really add value, then we need to find a better way to use enterprise business intelligence solutions to bring people together and have them collectively engage with the data they have and each other wherever they, or that data, may be. Think of how much more you know about your group of friends, family and old acquaintances on Facebook then how much you knew before. Imagine being that connected to the events taking place in your company: a marketing campaign just went live, a big deal in the forecast just moved out, a big order has just been placed, and how knowing these facts would impact your choices and decisions.

Out from the Shadows

When I spoke about my role as a user of analytics, I did so very much in the context of me as an individual within the SAP worldwide marketing organization that’s responsible for our analytics business.  I see myself as very typical of the type of person that should (and is increasingly trying to) use analytics to help better understand what’s happening within the business.  I do this by exploring my data and then present and visualize it in a way that allows me to take action and, more importantly, guide the action of others through collaboration.

The problem in many cases, I think, is that users like me define what we need but then continue to look at our data in a silo and in a shadow, hiding from the wider organization. We need to make sure that we have a platform for agile visualization that gives us what we need to do our jobs. It needs to be lightweight and easy to deploy while also being based on a solid foundation. We need strong governance and semantics across our data to ensure that when we do collaborate, we do so in a way that reduces confusion instead of increases it. Without a common understanding of information we are back to the age-old problem of spending more time arguing about the numbers then discussing what they mean.

In Anticipation of What Comes Next

In my third blog, I spoke a lot about the need to educate users on how analytics should be used. I don’t mean how we educate about the features and functions of an analytic solution or the way the UX works (although that’s still important.) I mean, how we actually educate users to make decisions and understand the way analytics operate.

This is where I think we have the biggest opportunity – we can deliver advanced analytics into the hands of users across the enterprise.  As we build the ability to predict what will come next into their day-to-day lives, and educate them on how to use and interpret this information, they will be much better suited to guide better and ultimately more profitable decision making.

My point is simple – if we can address all three of these areas: Enterprise BI, Agile Visualization, and Advanced Analytics (and not just one of them), we have a unique opportunity. In my mind, each feeds the other and each has the power to bring our teams together. For me, that’s what analytics needs to do, it needs to allow individuals to get the information they need, and then share their insights back with their team and the broader organization. Like Newton said “If I have seen any further it is because I have stood on the shoulders of giants.” We need to educate and we need to empower our users to work collaboratively. Only then will the full power of our collective insight be realized, harnessing the true power of analytics.

This is a huge topic and far too much for one blog. But this is good, as it means I’ve met the objective I set out for myself when I started. It gives me (and, by definition, my team) a cause to explore these thoughts further.

That’s exactly what you’ll see us doing starting today at the ASUG SAP BusinessObjects User Conference in Anaheim, CA. We’ll continue the discussions on our various blogs over the coming days and weeks. Let us know what you think…

Big Data Will Save the Planet!!!

Over the last few weeks, I’ve noticed a trend on Twitter where various folks are posting Tweets referring to articles and blogs about how “Big Data” will transform the travel industry, or Big Data will optimize marketing, or Big Data will revolutionize information security.  All are interesting posts, and all are pretty accurate, but even for me (a marketing guy) these types of headlines make my skin crawl.

Let there be no doubt that I’m all for getting away from talking about the technical aspects of managing Big Data or talking about ever-growing numbers of “V’s” to describe the challenge.  Instead, I much prefer to hear about the value and opportunity it presents. But can we please stay away from pithy headlines?

Big Data’s Value Doesn’t Need To Be Hyped

In my view, these headlines simply epitomize a lot that’s wrong with marketing hype around Big Data.  I know most Tweets are created to fit within 140 characters, but all I see when I read them are obvious statements that lack any depth because us marketing folks created them when we couldn’t think of anything better to say. It’s either that, or some internal marketing policy says that we always need to use an adjective to make it sound more impressive.

The simple fact is that Big Data’s value is real – so are the use cases and the resulting opportunities. Articulating that value has to be more beneficial than offering hype.

For the most part, when I talk to customers, they aren’t quite at the stage where they want to save the planet. Rather, they just want to find out how they can use the data and resources they have to perform better in their roles, across their teams, and ultimately their organizations.

Which article are you more likely to read?

a)     “Big Data to Transform Marketing”, or
b)     “5 Big Data Use Cases in Marketing”

Personally, I’d opt for the fact-based one, the one that sounds like it’s going to give me some real concrete examples, that’s going to give me some real ideas that I can put into practice.

Let’s keep it real!

What’s All this Talk About Finance? You’re the Analytics Guy Now!

A good friend and partner asked me this question at a recent event. I’ll protect the innocent by not naming them, I won’t even tell you which continent I was on, but what I will say is that it made me chuckle.

It came up as I mentioned I was co-authoring a book on a particular finance topic. I won’t plug it just yet as it’s not finished, and I have to be honest, I probably won’t be rushing to write another one again.

The truth is I do have a background in finance, more so than technology. I was at KPMG and then PwC before I found myself in the software business.  And even then it was with a company producing enterprise performance management solutions, aimed at the time primarily for finance, which was eventually acquired by BusinessObjects and subsequently became part of SAP.

So why is this relevant? Well, quite simply I happen to think that I represent the type of user most organizations, including SAP, need to reach.  I’m more than comfortable diving for a spreadsheet, more than comfortable looking at numbers (financial or otherwise), and while I may not be a data scientist, part of that finance education included quantitative statistics so I know a bit about the right questions to ask and how to interpret what the numbers are telling me. (Read my earlier blog on this topic). What’s more, the job I do today, irrespective of my finance foundation, is essentially marketing.

So with the growth in enterprise self-service BI and the expanding use of predictive analytics across the business, I’m the perfect example of the type of person that should be using analytics in my job and life, more and more.  But you know what? My friend has a point – when I was at KPMG I was a tax consultant. When I told people that they used to grimace. Finance was cooler, but being the analytics guy? Cooler still…thanks for the advice.

Quick Wins? Big Wins? Or Can I Have My Cake and Eat It Too?

Over the last month I’ve clocked a lot of miles heading from the UK to the U.S., to South Africa for the AFSUG events and back to Europe for SAPinsider, and during that time I’ve spoken to a lot of customers.  Those conversations, as you can imagine, have been pretty varied, ranging from questions about the overall analytics market, trends around big data and mobility, to more detailed discussions about how they are building roadmaps to drive richer and more impactful enterprise wide analytics.

What was interesting is that in a good number of these conversations I was asked a similar question which went along the lines of, “But we also want to show some quick wins. What do you think? Does that make sense?”

Well here’s what I think…

In my humble opinion, the recognition that quick wins should be part of a longer journey is good.  The reason for this is simple – quick wins alone are unlikely to make the most of the opportunity that a broader enterprise-wide analytics strategy can deliver.  Yes, you gain value; yes, you can do some cool things quickly; and yes, you probably don’t have to bang on too many doors to make them happen. But I believe they can only get you so far. At some point a bigger, broader change may be required.

That said, I also don’t believe that the delivery of a broad, enterprise-wide analytics strategy is possible without incorporating quick wins as part of the delivery process.  The sort of value they can deliver in a short space of time is the perfect example of what could be possible. That’s great when it comes to gaining the sponsorship of you key stakeholders, but it’s also critical when it comes to proving to the skeptics across the business that an enterprise-wide approach is possible without huge disruption or the loss of the flexibility they crave.

The trick here, in my view, is to find a way to best combine the two, where you can have your cake and eat it. Where you get the sort of quick wins the business loves and easy to use self-service analytics that can be deployed to solve numerous challenges quickly but at the same time contribute to a broader strategy. Enter the value of enterprise self-service analytics.

And that’s where I closed the conversations. “Yes it makes sense, here’s why and by the way… have I told you about SAP Lumira? You can download it free now…”