Understanding what analytics capability you need as a business is important and once done, you also need to understand where you are and how you can upgrade your team to the level required.
In essence, you need to understand the business big picture in order to build a high performing team that allows you to maximise business value.
Mature analytics teams are generally those that are:
Whereas less mature teams have the basic skills but are:
Once you have a view, you need to identify how you can move your team through the levels to reach the level your business needs it to be and the time that journey might take.
Finally and critically, do you have senior management commitment? This is probably more critical than any other element and the one that most businesses often only pay lip service to.
Are you ready for the change?
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Continuous Improvement and the importance of reinforcing Core Values.
No matter how good your data analytics practice is there needs to be a consistent approach to building the best team possible to derive the best value from your data analytics.
To do this, there are a number of key elements that you need to put in play.
It's important that all within the data analytics team work together for the common goals of the business and that they proactively share their skills and knowledge to support each other.
While you should expect your teams to work hard, you also need to be flexible to balance the needs of individuals with those of the business. Prioritising and getting the balance right between BAU work, projects and critical work allows you to maintain the balance between getting it right and getting it done.
Strive to be successful and deliver what you promise, recognise that team success is as important as individual success and always recognise success and reward it appropriately.
Ownership is important and individuals should be encouraged to look at the business and its values as their own and take responsibility for what they do and to be proactive in making things happen.
It is also important for the business that all are encouraged to look for inspiration inside and outside the business and that individuals aim to proactively learn new techniques and methods. This could then lead to individuals aiming to solve problems and offer possible options for resolution, rather than simply bringing a problem for someone else to resolve.
A key element of almost any set of values is integrity. Yet it is often one that senior leadership forget when looking at managing their patch of turf. Clearly what should be in play is that all should aim to do the right thing, to tell it how it is, promise what you can deliver and then deliver it.
At the end of the day it's the outputs that count. Therefore, it's important to instill the right values to aim to get it right first time by thinking ahead and juggling priorities to make sure you get the most out of each hour.
Any business that can deliver continuous improvement using some or all of the above has more than a good chance of creating a world class business and a first class data analytics practice.
Next up I will talk about how you determine the maturity levels of your Analytics team and how you move from basics to mastery.
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Last time I talked about how important it is to remember that while all businesses should be data driven, it is critical that the data referred to is 'business driven'.
And by that I mean that having the right data, structured in the right way will help you to facilitate and better inform your business decisions.
In order to develop this, you need to recognise the multi-facetted or multi-dimensional challenge that every business faces when trying to turn data into profit.
These core modules range in increasing complexity from putting the infrastructure in place to developing real time business decisioning.
A first class Analytics practice will address these 12 core analytical modules whilst also continuously developing their people, processes and technology.
In order for this to work however, it is important that the business leadership is fully supportive of the challenges that such a function faces when dealing with the continual demands for information from other business departments and the cost implications of incorrect prioritisation.
The best businesses in the world manage these challenges and that is why they are able to take that raw data the business generates and turn it into not just knowledge but profit.
The next element of creating a first class analytics practice is something that all good businesses and departments should follow, but many don't - Managing Core Values and Continuous Improvement.
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Following on from my blog about Laying the Foundations for a first class analytics practice, I thought I would expand next on the key enablers.
Analytics is a critical function for any world class business and the 3 key enablers in any such business are People, Process and Technology.
Perhaps not a new concept but it is an important one nonetheless.
It is important that you have individuals with the right investigative attitude and skill set who are also commercially savvy and technically proficient. Then you create a lean structure that has continuous improvement at its centre and enables individuals within it to believe and practice core values.
People with a can-do attitude that believe in analysis and the importance of extracting information that adds value to the business can and will add real value as long as you support them with process and technology.
Like any other part of the business, it’s important that the right processes are in place to help prioritise activity based on a value assessment and then create an appropriate analysis process and research library with established methodology for others in the team to follow.
Clearly, an appropriate project management system should be engaged together with a common analysis methodology and continuous training programmes.
Simply put, the process should begin with the end in mind and be methodological in its approach.
The technology you put in place should be appropriate to the current and near future requirements of the business. You need to look at the options and compare systems based on such elements as Speed of Analysis vs Accuracy, Standalone best of breed vs a Complete solution vs In-house build, Complexity vs Maintenance vs Benefits and Future Proofing or Scalability.
Once in place, core analytical modules can then be developed to undertake complex analysis such as modelling, segmentation, or cross product optimisation.
These key enablers combined with continuously developing your people, processes and technology provide a way of turning Data into Profit.
Next time I will expand on how turning data into profit requires the data function to be aligned to the business, supported by good process, analytical skills and technology capable of managing complex data.
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Brendan launched Blue Label Consulting in 2011. With innovative use of Data through AI, ML and other quantitative methods, he delivers robust analytics and actionable insights to solve business problems.