What am I talking about? I’m talking about our inability to translate breakfast, lunch and dinner rants into interoperable technologies that provide decision-makers with the right data at the right time for the right price. Why is this so hard?
30 years ago, I was told that data was king. It’s taken me three decades to fully understand the importance of that simple statement and the importance attached to someone’s need for information presented in the right way at the right time. Today, we think about all this as business intelligence (BI), which has become an enormous industry in and of itself. But it’s more than that.
It’s the ability to answer questions about customers, growth, profitability, supply chains, inventories, pricing and a whole lot more – instantly. Can we do this today? If the billions that companies are paying for BI vendors is any indication, we can’t. BI today is a technology, not a business solution.
Just the other day it happened again. In a discussion about the development of a company’s technology strategy, it became very clear that what the business wanted from the strategy was one thing: data. Did they care all that much about infrastructure, about the wonderfully reliable messaging platform, about the near-zero-latent network, about the upgrade to Vista?
Hell no. All they cared about was the ability to get data into their hands when they need it to make decisions about only three things: how to make money, how to save money, how to improve service. If the “strategy” could help them do one or more of those things they would be very happy. The rest, from their perspective, is boilerplate.
In many respects this is the ultimate conclusion to the “IT doesn’t matter” argument launched in 2003 by Nick Carr. I have said for years that Nick was half right – that operational technology has definitely commoditized but that strategic technology could still be a huge differentiator – when acquired, deployed and supported correctly. The business doesn’t want to discuss how elegant, secure, reliable or scalable the infrastructure is; they are obsessed with what technology can do for their ability to save money, make money and improve service.
Or, put another way, they are obsessed with their own performance and securing excellent employee reviews for themselves and their teams. Technology’s role is to make that happen, and in order to make that happen, we all need to focus – again – on data.
I used to draw cute distinctions between “data,” “information” and “knowledge,” you know, with information the extension of data and knowledge the end-result of collective information interpreted by knowledge managers. Sure, the distinction was cute and even accurate – but no one really cares about how I – or anyone – slice up definitions of the same thing.
I actually feel a little stupid (I’m the “stupid” in the “it’s the data, stupid”). I have been listening to the “data is king” and “friendly data” tunes for decades, but, unlike the Sade (“Your Love is King”) and James Taylor (“You’ve Got a Friend”) songs that I can remember like it was “yesterday” (another great song), I don’t seem to understand what the words really mean.
So here’s a simulated therapy session to help me through this conundrum:
Stupid (me): “So what does a CEO mean when he or she says: ‘I want friendly data’?”
Data therapist: “What do you think he or she wants to say? What do you think he or she means by ‘friendly’?”
Stupid: “You don’t know”?
Data therapist: “How would I know? … I just facilitate things.”
Stupid: “Do I get any lifelines”?
Data therapist: “Sure, it’s your money.”
Stupid: “OK, let me call a C-level exec … ‘C-level exec? Is that you? What do you need from me? What the hell is ‘friendly data,’ anyway?”
C-level exec: “You really are stupid. It’s so simple. Friendly data helps me make decisions. Friendly data is always there – accessible any way I want – an a Blackberry, an iPhone or a PC. Friendly data is diagnostic – it helps me understand the current state and enables me to play what-if games. Friendly data is historical and anticipatory. Friendly data keeps me out of regulatory trouble. Friendly data helps me up-sell and cross-sell. Friendly data is a window into my products, services and – especially – my customers. Friendly data is dynamic and real-time. Friendly data never sleeps. What else do you want to know?”
Stupid: “We call that business intelligence. It’s been around for years.”
C-level exec: “Call it whatever you like. I really don’t care.”
Therapist: “This is going very well, but our time is up.”
Stupid: “Same time next week?”
Stupid: “Not you, stupid, I want to keep talking to the C-level exec. I need to become them. I need to feel their pain – and then make it go away. I might just be getting it. It really isn’t about me at all. It’s about them and what they need – and they need data.”
C-level exec: “I’ll work with you, of course, but you really have to get smarter about all this. I just saw something about on-demand BI that caught my eye. There’s always someone who will listen. I’d love it to be you, but if you can’t get by your data/metadata/information/knowledge/extraction/integration neuroses, I will move on.”
Therapist: “I can cure him.”
Stupid: “I can cure myself.”
So let’s agree to screen all of our technology initiatives through a data filter. Let’s agree to start with business processes and three business objectives. Let’s quietly invest in data architecture and infrastructure without describing ad nauseum how wonderful our master data management is. Let’s collaboratively build dashboards and marry them with mobile computing. Let’s define the end game as real-time dynamic transaction processing. Let’s pretend we’re in a company cockpit and all we have are sensors, gauges, switches and displays to fly the company. Let’s stop being stupid.