It's so sad when you start getting geeky about technology. Other people are talking children, wine or movies and all I can rave about are my latest thoughts about data and how it should be positioned. I'm excited by it!
After helping businesses market and sell for over twenty years I discovered predictive analytics being used in farming to affect the health of cattle. Then how oil and gas were using the industrial internet to avoid loss of life disasters. Retailers were desperate to get the language of their target consumers right. The military adopting facial recognition to improve the rapport of ground troops with local foreign communities.
Data analytics, Big Data, The Internet of things, M2M. There are different names. Different meanings and different applications, but its here. Its here to stay. Here to help us be smarter and more specific in our decision making.
Sharing the same bed as all the cool applications is confusion. Businesses are all talking big data, analytics and myriad technology providers have moved in. Torn between wanting to be proactive and not having enough knowledge of the data industry, mistakes are made:
1) One department somewhere buys something - Silo thinking
2) Data is used to answer one question while the other 50 and looking at the whole supply chain (which is what you should do), gets ignored because that's a different department and adds complexity for both the organisation and the vendors selling to them. Not a holistic view
3) The availability of data may slap you in the face with a message that says you have been doing it all wrong. Who is going to bite that bullet? - Self preservation
4) The idea is to make or save money not just be sat with another spreadsheet gathering dust. Big Data often gets chucked at the IT department with all the focus on the technology and the "how" with a real lack of commercial planning
Using a process of Touch Point Mapping (TPM) I help businesses to navigate the challenges with their commercial objectives always firmly front of mind.
How do you start?
What do you get started with?
What does measure-evaluate-develop-repeat look like with data analytics?
How to accept and plan for some failure?
How to avoid getting carried away with the art of the possible and zone back in on what is commercially and culturally viable.
Retail & grocery. Architect. Construction. Engineering. Telecommunications. Print. FMCG. Healthcare. Education. Local Government.