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DataIQ Leaders briefing – The 4 habits of effective analytics teams

Based on conversations with more than 70 data and analytics practitioners drawn from 27 different organisations, this briefing identifies four habits which can ensure that the analytics team and its leader engage and deliver to the business effectively.

Habit 1 – Collaborating

Like knowledge management, analytics is a “contact sport” – when analysts interact regularly with each other and also with lines of business, ideas are exchanged, opportunities identified and the temperature of the business as a whole better understood.

A collaborative senior manager will also benefit from being perceived as a trusted adviser and provider of data which is a source of truth. This is especially the case if the analytics leader makes it clear that feedback is welcomed and acted on. 

Analysts need to have a common frame of reference, such as a set of working practices and language, which they all adhere to. This ensures that collaboration becomes frictionless as there will be no barriers through misaligned concepts or processes.

Partnering analysts with specific business executives, either through routine meetings or by embedding them into the line of business itself, is the sign of a highly-collaborative team. 

Adopting collaborative tools through which ideas and information are shared is a key supporting resource for this habit.

Habit 2 – Communicating 

Analytics can appear to its internal customers as something of a “black box” which generates models through an invisible, quasi-magical process. Often, this is a direct consequence of limited communication by the analytics team with its stakeholders.

Effective communication means adopting the terms and language of the business, rather than expecting business executives to understand the technical language of analytics. Data storytelling and data visualisation are key tools in this process to translate the numerical process of data analysis into a language-based narrative which stakeholders can understand. 

Communication within the team and between the team and its leader is also essential. This is best achieved through a combination of formal meetings where information is exchanged in a structured way and by creating an informal culture which encourages casual interactions. The physical set-up and appearance of the analytics workplace can help to enable this. It is also a useful media space for internal communications to be distributed.

For analytics leaders in particular, a further step is essential – making the link between what the analytics team has done and successful business outcomes. it is often assumed that simply doing good work will lead to recognition by internal customers. But this is very rarely the case – those stakeholders need to be constantly informed, educated and reminded of how central analytics is to the success of their own line of business.

Habit 3 – Championing

As leader of an analytics function, a key part of the role is to champion what it can do for the business, solving current problems and identifying opportunities. While there may already be top-down buy-in to the use of data and analytics to optimise processes and support new ones, this can not be taken for granted.

Instead, it is important habitually to get behind the big issues. All CEOs have a list of priorities for the organisation which they intend to address. Typically, these will include cost reduction or incremental revenue, but might also cover sustainability, diversity, customer experience and more. If the function leader can champion these goals and offer support and solutions, it will reduce the risk of becoming exposed as a cost centre, rather than being recognised as a value-driver.

Providing confidence in the impact being made by analytics is just one dimension of leadership – a truly effective leader must also have the habit of honesty. True champions are willing to admit when something is wrong or has not worked, while committing to discovering why this has happened and putting it right. 

Learning to say no is also the mark of a champion. This means closing down requests that are outside of agreed parameters or which can be shown to hold little real benefit. It also means admitting not knowing the answer in every circumstance. Showing a positive attitude towards such gaps and a keenness to close them as swiftly as possible will gain support and build real authority.

Habit 4 – Challenging 

One of the toughest habits for analysts and leaders to adopt is that of challenging the business within which they work, especially when it is a senior executive they need to contradict. Yet without this behaviour, the analytics function will only ever be reactive, rather than active as a proactive change agent.

The need to act in this way is probably most apparent in relation to the myths which tend to propagate across organisations. Examples of this might be a belief about “hero products”, the typical customer profile, what the real profitability of a service is and so forth. Typically, these grow unchallenged and become the basis for the political power of one line of business which happens to own these successes.

Once analysts get to work examining the available data, they will often uncover contradictory truths. This is especially true of data science if it is given free licence to look at the organisation end-to-end. Few of those business myths survive this examination.

It is the mark of a mature analytics function – and of the organisation that hosts it – when it becomes able to behave in this way. Relatively few functions have achieved this status as yet. But one of the key steps towards challenging in this way involves the use of data. Giving access via self-service tools can help because it quickly surfaces the reality of any given issue. As one DataIQ Leader put it: “Give them the rope and they will either skip or hang.”

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