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Act at speed without risk

Last November I was asked to present at Enable 2016 in Auckland. The theme was Enabling business transformation through the IT function and was attended by CIOs, IT Managers and other leading ICT roles.

Tim King (Cucumber CTO) and I presented our topic on Enabling Invisible data. The premise being that companies are challenged by data that is often trapped and therefore invisible. This data can be in physical assets such as PLC’s, legacy software systems and inefficient manual processes where data is often captured on paper if you are lucky.

Tim and I went on to highlight that even when companies do have visibility of the data, if they are unsure of the right questions to ask of the data they won’t gain many benefits. In fact a Forbes survey recently found that only 27% of executives thought their big data projects were successful so what is going wrong?

This led me to think further about this whole “big data” thing we have been overwhelmed by. It is true that data is being generated at an exponential rate (2.5 quintillion bytes per day and growing according to IBM) but for all companies looking at data no matter how big or small, it seems to me that not only do you need staff who understand how to manage and analyse the data, but they also need to understand the business purpose, its objectives, its customers and how the data findings apply directly to them. Plus they need to do this at speed to keep ahead!

Even when you have invested in skilled staff to interpret the data with required domain expertise the process can often be painstakingly slow due to inherent ICT data management challenges and consequently opportunities may get missed.

Being able to act at speed is a key prerequisite to taking advantage of the data. This means that there needs to be a coming together of business disciplines to achieve the benefits. Clarity of business purpose at C-level helps the data scientist. This must be matched by changes in organisational structures that help move the organisation from having siloes - “ponds” - of data to an integrated approach to business data – “lakes”. ICT functions need to enable a ‘fast data’ and ‘agile’ capability as the business needs to see what’s going on in the market and respond quickly across business functions if it is to stay competitive.

In the current climate, the ability to model multiple ideas against near real time data then rapidly test hypothesis is critical. A recent Cap Gemini whitepaper highlighted that 77% of decision makers want data in real-time. Failing fast, or where you find value, scaling quickly to meet the needs of customers are the new goals.

This means ICT teams need to operate in a very flexible way to help business prove value in the shortest time-frame. It’s all very well pre-planning multi-year ICT programmes but they may be redundant in 12months as there is no longer a business.

Three “low-risk and fast approaches” which ICT teams should use consistently with business to test ideas rapidly include:

Protoyping: which for us means using interactive wire framing techniques to test a solution design with real users quickly and see if the response to your idea is positive. This works to really understand your customer’s problems and test your solutions iteratively and quickly without the need to build the technical solution.

Proof of Concepts: which at Cucumber means testing out a way to resolve a specific technical problem area or issue. For example the key data you need to access quickly in order to gain new insights may prove challenging to extract based on your current process and technology. It’s useful therefore to focus on whether you can solve a key issue that is critical to testing your hypothesis. In this case traditional technology constraints from policies should give way to innovative tools that may help release the valuable data.

Minimum Viable Products: which means producing a real usable solution that aims to solve specific core customer problems but without the major capital risk of a full development. This can be a rapid response to a competitor’s move in the market or a test move into a market. Airbnb is a classic example of an MVP. There was a design conference coming to town, and the founders decided to open up their loft as cheap accommodation for conference attendees who had not had much luck with the hotels nearby. They took pictures of their apartment, put it up on a simple website, and soon they had 3 paying guests for the duration of the conference.

So, yes Big Data is becoming the raw material of business but it needs;

  • you and your staff to know your business purpose and objectives
  • you to organise your business in an integrated way and get away from data siloes
  • your staff to be very comfortable with both analysing data and ideation techniques
  • your ICT team need to be flexible and have the agility that enables you to test your ideas with your customers at speed and with low-risk.