Reusing Analytics

Unlocking the enterprise value of data is akin to sharing baby clothes.

My partner and I live in NYC with our daughter. We have good friends who live in Canada whom we often speak to, as they have a daughter 6 months older than ours. One of the great things about this relationship is not only do we get great advice and anecdotes about the fun stages upon us, but we get clothes and useful items donated to us - for free! What’s key in making this work is that our friends know enough about us to do this effectively; they know the age of our daughter and therefore the approximate size of coats, sweaters, pants etc. They know the time of year it is so what clothing is going to be most relevant and when (it’s getting cold in NYC!); they know the gender of our child and therefore perhaps the right colour of clothing - although there is way too much pink in my house right now(!) and finally, our family lifestyle and activities - we love spending time outdoors so we get lots of great warm jackets and outdoor play clothes.

This context allows our friends to share clothes and other items effectively - knowing what will be helpful for us and when.

Imagine if we could do this with data across teams inside our organisations? If we knew what insights and models would add most value, to the right team at the right time.  This sort of effective collaboration would unlock huge value in our data.

In a December 2016 report on the state of data analytics McKinsey concluded that slow progress was being made despite large investments in technology because companies “have failed to make the organizational changes required to make the most” of big data. Despite a strong desire for success these expensive big data investments are not producing meaningful results.

Unlocking the value of analytics

I was recently the Chairperson at the Chief Analytics Officers Fall event and the subject of unlocking business value in data and analytics came up again and again. "How can we leverage the collective intelligence of our organization and embedded analytics teams?" "How can we maximise the utilisation of analytic tools and skills across the organisation and break silos of best practice?"  The conversation came back constantly to people - business and analytics interactions and ways of working. 

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Here are some things to consider as the driver of change in your organisation: 

1. Business context

Embedded analytics teams was a popular model and provoked much discussion and the sharing great success examples.  What is critical here is that such analytics team members obtain the right business context. “The worst thing that could happen is that it is seen as a request to the analytics department” was a comment that stuck with me.  

Rather, working in an agile and iterative way is most effective; clarifying the business challenge at the start of the project and checking for alignment throughout.  This can work through an outsourced model with the right tools. Don’t rely on email and assume that everyone is on the same page - challenging for clarity and achieving context is key.

2. Ways of working - from dashboards to structured thinking at scale

We’re starting to realise that the promise of Business Intelligence tool providers is falling short - specifically with self-serve analytics (very different from self serve reporting). “Strapping a pretty dashboard on the end of a poor process is not good enough.”  Instead we need to support business teams to be hypothesis-led in their thinking and list and challenge their assumptions. This is a step change away from asking for a report or as an analytics leader said to me recently "moving away from being stick-fetchers for the business”.

3. Asking better questions

The skill for business and analytics teams will be to quickly and effectively identify their gaps in understanding. 

As a former British Commando Intelligence Officer we often used the words “Be the first to Understand, first to Decide and the first to Act.  Here is where data drives better decisions in business teams.

4. Sharing intelligence

 

 

So, when business leaders across your organisation are working effectively with embedded analytics teams, coming up with better questions and insights, how do we effectively share and reuse this insight?

5. #tagging business areas enables us to push insights to teams where they will add value.  As per my example at the start of this blog, knowing what is relevant to other teams allows us to unlock the collective intelligence of our business teams and effectively reuse analytics.

6. Using search, teams can access insights at multiple levels - groups, business tags, and hypotheses. This familiar technology to users allows leaders to discover across their colleagues and teams.  This is where the power of data and the organisation is unlocked!

Empower your teams to take action now. Understand more about Connectworxs, which comes from over 15 years of operating in this space.

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