David Dumeresque explores what organisation leaders need to address from a talent perspective to capture the full value of data.
What does big data mean to start-ups and small businesses? We read a lot these days about how big data will create new growth opportunities and how it will create sustainable competitive advantage, providing the means for companies to outperform their peers.
But we also read that big data requires vast investments in big data frameworks, analytical software, data warehouses and data scientists who can build complicated models to guide companies through the maze. The size of these investments often exceeds the financial abilities of many small companies.
So, does that mean big data lies outside the realm of small business? Not at all.
The December 2013 issue of the Harvard Business Review contained a very interesting paper titled ‘You May Not Need Big Data After All’. One of the arguments put forward by authors, Jeanne Ross, Cynthia Beath and Anne Quaadgras, was that many companies don’t know how to make the most of the data they already have embedded in their core operating systems. They invest heavily in big data but fail to get a satisfactory return on that investment. Until executives learn how to use data and analysis to support their operating decisions, they will not be in a position to benefit from big data.
For all companies, the starting point is to develop a culture of evidence-based decisionmaking. For years, we have used market research to compete more effectively in our marketplace. What has changed significantly is the substantial increase in the source of our data. We are now creating new information 50 times faster than we did ten years ago, generating a staggering 2.5 exabytes of data every day and the volume is growing. Still, the need for evidence-based decisionmaking has not changed.
Keeping abreast of technology
There is no doubt that with the volume of data being generated, as well as the different formats of the data (structured and unstructured), companies will need to make changes to the way they operate if they are to take advantage of this new-found wealth of intelligence. With the rapid advances in technology, business leaders must ensure that management practices keep abreast of their technology platforms. This will certainly require the hiring of appropriately qualified and experienced staff, plus an investment in training and development programmes.
But small business doesn’t need to compete head-on financially with big business for people like data scientists, data architects or PhD data analysts. Compensation is important, but for those with moderate human capital budgets, there are a number of areas where small business leaders can succeed.
First, data gurus are motivated to work in an environment where they are constantly challenged, in companies that are innovative, have highly interesting data sets and are willing to invest in the new technologies. Large companies can pay top market rates for a data scientist (circa £200,000 to £300,000), but if the job is boring or they feel their skills are not being fully utilised, they will move on quickly, seeking more nimble and agile workplaces where they can be closer to the decisions.
What also sets top data specialists apart is their curiosity. They are always looking for patterns in data that seem invisible to others. It may take them some time to develop appropriate algorithms to enable them to detect these patterns, but eventually they will find them and the rewards will be substantial. Appealing to this inquisitiveness increases the recruitment and retention success rate. Most importantly, they need (like anyone) to feel valued, allowing them to participate in the decisionmaking process rather than being hidden away in a dark corner, allows them to feel valued (and also gives the company even better insight).
The surge in demand for data scientists has been well documented and the number of people with deep analytical experience is shrinking. One effective option for small businesses is to recruit at the level of experienced data or software engineer. What these people may lack in mathematical theory and data modelling techniques is often more than made up for by being grounded in the real world.
The big data highway
Good data engineers will have the experience to understand big data analytics applications, take the data insights generated and turn them into operational reality. Many will also be experts with big data frameworks such as Hadoop and Spark, along with scale-out NoSQL databases such as MongoDG, Counchbase and OrientDB. These skills will be sufficient to get small businesses effectively started down the big data highway.
Developing an effective data platform is not simply a matter of obtaining the intelligence from a variety of different sources and undertaking the appropriate analysis, but ensuring data quality standards are maintained, getting the material into the right formats that will enable evidence-based decisions and getting the information to all relevant personnel in the organisation quickly.
There are skilled people other than just data scientists who can provide the right big data support for small businesses, even though in the longer term, business leaders may need to provide the necessary training and development to take these people to the next level.
The key, however, is to act sooner than later. With the numbers of available top-end data scientists across the globe diminishing, skilled data engineers will be next on the list. And when you are successful in your recruitment, ensure that you do everything to hang on to your talent.