From digital transformation to big data and analytics, the internet is littered with buzz words and promises that technology is the answer to revolutionising business and delivering better results.
By Malebona Mokhutsoane, solution advisor for analytics, and Dumisani Moyo, head of mid-market: southern Africa at SAP
But what does this mean in practice, particularly for small and medium size businesses? One could reasonably argue that their bigger siblings have recognised this and to some extent, managed to leverage the benefits of technology to drive better customer experience, improve efficiency and deliver better business outcomes.
This article explores how SMEs can incorporate augmented analytics into their digital transformation strategies and operations to drive better business outcomes.
What is augmented analytics?
Augmented analytics is the use of technologies such as machine learning, artificial intelligence and natural language processing to assist with data preparation, generating insights and presenting those insights in a way that augments how people explore, analyse and utilise data.
The machine learning component automates the analytics phases of data preparation and the generating of insights. Natural language processing enables business users to get insights from data without a deeper knowledge of the underlying coding languages. As a matter of fact, natural language processing is the technology behind digital assistants such as Siri and Alexa.
Augmented analytics is not intended to substitute humans, but rather to enhance our interpretation capabilities when working with large and complex data sets and facilitates the generation of business insights from cold data.
Augmented analytics in SMEs
A study by Accenture found that 97% of the data that is collected in most companies is never revisited, never used to drive operational efficiencies, and by effect, not being used to improve business outcomes. The same study pointed out that more than 87% of companies have low levels of maturity in terms of their business intelligence and analytics capabilities.
SMEs need to prioritise data and treat it as an asset. They need to leverage both operational (O-data) and customer (experience-, or X-data) to drive better business outcomes and to create sustainable competitive advantages. Through analytics, SMEs can use data, specifically the intelligence and insights it presents as a basis for driving innovation, business agility, reducing operational risks and developing new revenue streams.
In the words of Michael Dell, “digital transformation is not about IT … it is a boardroom conversation, driven by CEOs and line-of-business executives, focused on answering some very big questions: How do you fundamentally reimagine your business? How do you embed sensors, connectivity, and intelligence in products? How do you reshape customer engagement and outcomes?”
The data driven enterprise
Many technology pundits have dubbed data as “the new oil”.
The notion is predicated on the fact that raw oil isn’t as valuable as the final products that are produced after it is processed. In the same way, data isn’t as valuable as the insights that are generated once it is analysed.
Once analysed and refined, data becomes a valuable decision-making tool, enabling companies to quickly adapt to changing market conditions, identify new markets and opportunities and make their businesses more resilient and less susceptible to market disruptions such as Covid-19.
The future of analytics
Whether looking for something to order on Uber Eats or a movie to watch on Netflix, augmented analytics has become well entrenched and pervasive in our everyday lives.
You do not need to think hard about what to eat or what movie to watch, technology does that for you in a split second. Customers have become accustomed to this level of convenience in their personal lives, and it is only a matter of time before they start demanding the same in their professional lives.
SMEs need to see technology as a crucial cog and enabler in the value creation process.
The emphasis should be on integrating technology, such as augmented analytics into all aspects of the business, especially the value chain and value-creating processes of the company.
This is crucial to ensure that technology supports broader and long-term business imperatives such as innovation and improving operational, business and customer outcomes.