An occasional series in which a review of recent posts on SmartData Collective reveals the following nuggets:
It doesn’t have to be that way
Ideally, corporate restructuring means establishing a process to allow organizations to continue their operations using their existing systems. IT systems reconciliation simply cannot get in the way of running business operations. All too often, the answer is, “Replace their systems with ours.” This statement means that the new organization should re-engineer its business. This simply takes too long.
Is it really “our” data?
Knowing the big differences between what we (as data miners) are ‘able to do’ regarding insights and personal information (particularly in mobile telecommunications) and what we ‘should do’ is very important. Years ago the industry passed the early developmental stage of storing data; in recent years we have learned how to understand the data and convert it into useful insights. I still think that many data miners don’t realize how important (now more than ever before) it is that we act responsibility in the use of the personal information we obtain from ‘our’ data.
An occasional series in which a review of recent posts on SmartData Collective reveals the following nuggets:
It doesn’t have to be that way
Ideally, corporate restructuring means establishing a process to allow organizations to continue their operations using their existing systems. IT systems reconciliation simply cannot get in the way of running business operations. All too often, the answer is, “Replace their systems with ours.” This statement means that the new organization should re-engineer its business. This simply takes too long.
Is it really “our” data?
Knowing the big differences between what we (as data miners) are ‘able to do’ regarding insights and personal information (particularly in mobile telecommunications) and what we ‘should do’ is very important. Years ago the industry passed the early developmental stage of storing data; in recent years we have learned how to understand the data and convert it into useful insights. I still think that many data miners don’t realize how important (now more than ever before) it is that we act responsibility in the use of the personal information we obtain from ‘our’ data.
Who is that masked man?
I had the novel experience today of discovering that someone set up a Twitter account for the sole purpose of harassing me personally. I’m not sure what exactly I did to deserve this honor, but I’m amused by the personal attention, since I’m hardly a Twitter celebrity. Perhaps it’s someone I know, conducting a social experiment to see how I’ll react. Ah, the wonder of online anonymity.
The mega-tech vendor and innovation
With all the consolidation and the emergence of the mega-vendors, there’s a lot of talk about innovation in the tech space and specifically how the new mega-vendor environment stifles innovation in tech. There are two types of innovation – continuous and discontinuous – and in understanding where our industry is moving it’s important to note the difference. Continuous innovation happens in a steady path of improvements to existing product lines over time… Discontinuous innovation is the radical leap-frogging of a current industry norms: things like client/server over mainframe and SOA are good examples in the enterprise space. The mega-vendor model feeds off of continuous innovation while startups often feeds off of discontinuous innovation. I think both of these types of innovation are important in a maturing industry like tech, and in fact they seem to continue in a healthy way today.
A world of visual possibility
Don’t get me wrong: a one-page dashboard is often an effective way to create “a visual display of the most important information needed to achieve one or more objectives.” But with streaming video, interactive visualizations, podcasts, Kindles, smart phones, video projectors… is it really necessary to limit ourselves to 8.5″ x 11″ piece of paper? Or might we open ourselves up to some more creative solutions to sharing the numbers: a short movie, a few slides, a short text narrative, or 140 characters?
Where the problem may lie
There is a tendency, especially in the US and Europe, to believe that technology can solve the difficult problems that we face. Technology, especially in corporate settings, is viewed as the cure-all or silver bullet that overcomes all the obstacles that have been encountered with data in the past. But the problem with our comfort level and faith in technology is that often the critical success factors of a solution lie with people and policies. And often there’s a little bit of politics thrown in to keep things interesting.
Measuring the customer relationship
While as marketers we typically look at the entire size of our database to determine if we have enough contacts to convert to leads, if those leads are weighted towards a low number of companies, or they are not the right contacts, then our efforts can be wasted. With the cost to acquire customers and contacts expensive, having a mechanism to determine when to purchase lists and how much to purchase will refine the amount of resources and budget needed. In addition, messaging and engagement strategies can be modified to align to the type of relationship outcome you intend. So, rather than thinking about personas when you need to target, think about them strategically and as an indicator of the strength of relationship with your customer.
