Why is it so difficult to deliver consistent, effortless customer service interactions across communication channels and touchpoints. A fundamental reason has to do with how companies are internally organized. In many companies, sales, marketing, and customer service are discrete functional silos that don’t necessarily share the same technologies, business processes, data, or even the same definition of measures of success.
Let’s take a quick look at the organizations that make technology purchases for customer service. Obviously, the customer service operations group makes most of these purchases. Yet marketing and eBusiness organizations also purchase many technologies that are valuable to customer service such as social listening solutions, enterprise feedback management solutions, and social media technologies. Here are some numbers to back this up: in a survey of eBusiness and channel strategy executives, 91% said that they were responsible for the website and digital channels like email, chat, and web self service, and another 69% said they were responsible for the mobile operations, including the required technology purchases.
How much would it cost to establish a taxi dispatching system in a city of 20 million people, with nearly 66,000 taxis jamming the roads? Consider that Singapore, with a population of about 5 million, has spent tens of millions of dollars to build a customized system with screens and sensors installed in almost every taxi and a large-scale call center to support it.
Now with the wide availability and affordability of smartphones, entirely new innovative approaches that are light on infrastructure can be employed to reduce cost and time-to-value. A good example is a mobile application recently launched in Beijing called Didi Taxi that works like this:
Passengers and drivers download the app. There are two versions, currently available on both iOS and Android. Drivers download the app to accept orders; passengers download the app to order taxis.
Passengers bid for taxis through their mobile phones. When a passenger opens the app, they see their current location on the map and the density of available taxis nearby based on the GPS tracking on both passengers’ and drivers’ devices. Passengers then use their voice to specify their exact location and destination, and — most importantly — how much extra on top of the metered fare they are willing to pay (normally ranging from $1 to $3).
Taxi drivers confirm the booking. The system automatically broadcasts the message to all nearby taxis (within either a 1 km or 2 km radius) based on the density of nearby taxi drivers using the app. The first driver to respond within 90 seconds will get the order. If no drivers respond, the message goes out again to all drivers in a larger radius.
Leading-edge executives at organizations drive growth, innovate, and disrupt industries through emerging technologies: social, mobile, cloud, analytics, sensors, GIS and others. 85% of executives in a recent survey shared that “the need to drive innovation and growth” would have a moderate or high impact on IT services spending. But, today’s technology buyers face a fragmented, fast-moving landscape of niche technology and services providers in newer spaces (social, mobile, cloud) as well as new offerings from their largest global partners.
Often the leading- and bleeding-edge disruption comes from business stakeholders, rather than IT or sourcing executives; sourcing executives struggle to keep up with the fast pace of change that business demands. Our research shows that this fragmented, divisional, silo approach to buying (often under the radar screen) can create risk and go against enterprise IT strategy decisions.
To help their organizations navigate through these emerging options, we have identified three key principles of IT sourcing strategy:
Change the rules for working with vendors and partners. To thrive in the world of digital disruption and to enable sourcing of emerging technologies and services that drive digital disruption, sourcing strategists must create new rules for working with technology partners. They must increase the emphasis on innovation and differentiation and treat partners who excel in these dimensions differently from other tiered suppliers.
We all work very hard to make our BI initiatives, programs, platforms, applications, and tools very successful. We need a break. And what better way to relax than to joke about what we do? So... as my favorite Monty Python’s Flying Circus bit goes, “And now for something completely different [in BI]”:
Q: What’s the ROI/cost to achieve a single version of the truth?
A: 42 (compliments of my other favorite medium, Douglas Adams’ Hitchhiker’s Guide To The Galaxy).
Q: How many BI pros does it take to screw in a light bulb?
A: None — it’s an appliance.
Q: How many BI pros does it take to screw in a light bulb?
A: It depends. How do you measure/analyze/report on success?
Looking for lots more to brighten up our BI days, so please post away!
Why? What organization couldn’t benefit from making better decisions? Just ask the Obama campaign, which used sophisticated uplift modeling to target and influence swing voters. Or telecom firms that use predictive analytics to help prevent customer churn. Or police departments that use it to reduce crime. The list goes on and on and on. Virtually every organization could benefit from predictive analytics. Don’t confuse traditional business intelligence (BI) with predictive analytics. BI is about reports, dashboards, and advanced visualizations (which are still essential to every organization). Predictive is different. Predictive analytics uses machine learning algorithms on large and small data sets alike to predict outcomes. But predictive is not about absolutes; it doesn’t gaurentee an outcome. Rather, it’s about probabilities. For example, there is a 76% chance that this person will click on this display ad. Or there is a 63% chance that this customer will buy at a certain price. Or there is an 89% chance that this part will fail. Good stuff, but it’s hard to understand and harder to do. It’s worth it, though: Organizations that employ predictive analytics can dramatically reduce risk, disrupt competitors, and save tons of dough. Many are doing it now. More want to.
Few understand the what, why, and how of predictive analytics. Here’s a short, ordered reading list designed to get you up to speed super fast:
I’d not been to Norway for 32 years (I’m now embarrassed to say), so I really didn’t know what to expect as I travelled to the annual itSMF Norway conference in Oslo last week. I certainly didn’t expect the high price of just about everything; and I wondered if I would get a true picture of Norway in an airport hotel (in Oslo) with over 600 IT and IT service management (ITSM) professionals.
Now this is where my blogging could get me into trouble (or even more trouble), as I make a few personal observations as well as ITSM observations. But please humor me – they are all said in a very positive manner as I wonder what I missed in the Norwegian-language sessions and what those outside of Norway miss everyday. I’ll also write a second blog to cover some of the valuable content as soon as I make time.
My initial observations …
Firstly – “Wow, over 600 attendees for a country the size of Norway.” According to Wikipedia, Norway has five million citizens. You can do the math (or, as I would say, “maths”) relative to other countries. We have 63 million citizens in the UK …
Earlier today I was fortunate enough to participate in a BrightTalk webinar on the future of IT service management (ITSM) with these fabulous gentlemen:
If you want to watch the webinar on demand it can be found here (you will need to register if you are new to BrightTalk). What you won’t get with the on demand webinar (I think) is the full set of audience poll results, so I've included them here.
As we know, citizen engagement is a top priority of governments around the world. Many are launching digital outreach projects such as Adopt-A-Hydrant(pictured to the right). This is good news for both their citizen and business constituents (as well as for the application and platform vendors). Engagement is good. But what is really the best way to do it? What form should these projects take? How should the applications be designed? One way that has proven successful is the game.
As architects, we all know the importance of context. The right architecture for one context – say, an organically growing company – doesn’t work for a company growing by acquisition. The right technology strategy for a medium-size American company doesn’t work for a China-based one.
Well, the context for enterprise architecture itself is changing. We’ve got The Age Of The Customer forcing companies to transform outside-in. We have what is called technology consumerization – our business users have access to ever more powerful technology solutions independent of IT. We have digital-fueled business disruption, as described in James McQuivey’s book, Digital Disruption. And all this is driving the demand for greater business agility – the ability to quickly sense and adeptly respond to new opportunities and threats in their context.
What a great opportunity for enterprise architecture programs! But this is only possible if they shift from a focus on cost to a focus on opportunity, change from controlling to enabling technology, and adapt their practices to the need for quickness with “just enough insight.”
What do Google's Gmail, Ericsson's #1 telecom switching systems and Southwest Airlines' Ticketless Passenger Travel all have in common? Yes, they're all spectacular business successes, but what most people don't know is that they're also the direct result of employees working on their own time to solve problems and innovate above and beyond their daily tasks.
Here's another perspective on this reality: What science knows and what business does are 2 different things. These words from a TED talk from Daniel Pink were echoing through my cranium as I polished off my second glass of my brother's famous 1000 calorie-a-glass eggnog last Christmas Eve. When an idea is intriguing enough to occupy my thoughts on Christmas, it's gotta be good.
What got me noodling about all of this was a few days before Christmas, I was asked to come up with ideas for our May Forum on how workforce computing can drive better customer outcomes, and Dan Pink's "Drive: The Surprising Truth About What Motivates Us" which I was reading at the time gave me some fresh fuel to spark my synapses. Pink draws his inspiration from the work of Mihaly Csikszentmihalyi - a former University of Chicago behavioral psychologist now at the Drucker Institute, famous for his work in uncovering the conditions necessary for people to be intrinsically motivated to do their best work.