‘Big data’ is a buzzword right now, and for good reason: collecting internal and customer data helps businesses to see patterns of behaviour and preferences so they can provide better customer service, and target their products and services more effectively.
By analysing their data strategically, businesses can also pinpoint their own strengths and weaknesses more successfully, and improve how they plan to move ahead of their competitors.
A recent Forbes Insights survey revealed that big data and analytics had a significant, measurable impact on revenue for two thirds of respondents. This means businesses not currently embracing data analytics may be left behind.
The goal for many businesses is to become sentient. The sentient enterprise can listen to data, analyse it and make large-scale, autonomous decisions in real time. These businesses evolve constantly as their intelligence becomes more sophisticated.
Becoming sentient lets businesses to improve agility, responding to the world in real time and delivering the best solutions for both employees and customers. It fosters collaboration, leading to more useful insights across the business.
Importantly, a sentient enterprise makes decisions autonomously, which lets businesses reduce risk and contain costs, even as they improve their agility. This is a key goal, especially for small to medium-sized businesses looking to do more with less.
However, with so much data and so many analytical techniques to explore, the biggest challenge for many businesses is knowing where to start.
Initially, businesses need to look at their data analytics maturity, and then compare themselves with their competition and with other market sectors. They need to do so in an objective way because many companies claim to be far further deployed than they really are.
This is important because the more mature a business is at using data analytics, the more successfully it can tackle tough decisions to keep performing well.
The focus shouldn’t be solely on how to improve the collection and analysis of data. It’s also important to explore how to use these resources to drive business change and improve customer relations.
For data to be useful, it must tell a story. To decide where to focus data and analytics resources, businesses should ask six key questions:
1. What current challenges is the business facing?
There is almost no limit to the questions that can be answered using analytics.
However, to avoid wasting resources, it’s essential for businesses to clearly understand exactly what questions to ask.
To understand the various challenges the business is facing, the analytics team should initially engage with and understand the drivers of each major business unit.
2. What is the value of addressing each challenge?
Not every challenge can be addressed as a high priority. To justify the effort and expense of solving a particular challenge, it’s important to understand its impact.
Therefore, it’s necessary to rank each challenge according to how it currently affects the business, and how the business will benefit once the challenge is solved. This requires understanding the costs associated with each challenge.
3. What data is needed?
Knowing the questions that need to be answered makes it easier to see whether the required data is already being collected, or if the business needs to start collecting that data.
4. What analytics are required?
With a clear understanding of the questions and the available data, the team can then decide what analytics are required.
This can include analysing social media mentions, purchasing data, supplier lead times, or customer complaints. The team must pinpoint whether it has the tools in place to facilitate this analysis.
5. How complex is the work for the required analytical insights?
The business should now understand how complex it is to develop the required analytical insights.
This will determine whether the business can complete the analytics in-house with existing tools, or if it needs to hire new staff, train existing staff, or outsource the project.
6. Is subject matter expertise available?
Analysis will be more useful if there is a subject matter expert available to help direct the line of inquiry, interpret the results, and suggest ways to turn insights into actions that drive business change and strengthen customer relationships.
Without a subject matter expert, the business is essentially flying blind. Choosing projects where subject matter experts are available is highly advisable.
The answers to these six questions should be mapped onto a matrix: one axis indicates “expected value” and the other axis indicates “level of difficulty”. This will illustrate where the business should focus its resources.
Completing this exercise effectively requires the insight of analytics experts, data owners, IT infrastructure experts and functional business leaders who can identify ways in which data can improve performance and build stronger business and customer initiatives.
The way this expertise is combined will shape how the data is used. Importantly, businesses must let the data tell the story, and not be prejudiced by any preconceptions of what causes the issues in question.
It’s crucial to set priorities based on key business objectives, and then ensure those goals are achievable given the data and analytics skill sets currently in place.
This exercise will give the business a clear roadmap. It can then see which projects to address immediately, because they’re both valuable and achievable, and which projects to schedule to scale up and re-use the initial successes.
Once businesses allocate resources to the right projects, and the insights start to flow, they can gain significant benefits, including becoming a more sentient enterprise.
Alec Gardner is the general manager of Teradata Advanced Analytics, which provides end-to-end solutions and services in data warehousing, big data and analytics.
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