We conducted a ground-breaking survey of the UK’s data and business professionals to get a snapshot of the state of the world of data, uncover some of the issues facing the industry and get a sense of the changes on the horizon. The results were enlightening, and in some cases, very surprising.
1. Not waving but drowning
The state of data 2015
March 2015
2. The state of data: where are we now, and more importantly – where are we going?
When we conductedour survey of business
professionals, we set out to achieve three key objectives:
• take a snapshot of the current state of the world of data
• uncover some of the most pressing issues facing the Information
Management industry
• get a sense of what changes may be on the horizon
What we found was enlightening, and in some cases, quite surprising.
More than ever, data is the engine driving business. As recruiters
specialising in the field of Information Management and BI, we know
first-hand that the number of businesses across all sectors that consider
themselves to be ‘data driven’ is growing every day.
We expected to discover that robust, accessible, useful data is being
harnessed for a myriad of purposes: operational improvements,
increased understanding of customers, or positive business outcomes
such as increased revenue.
Instead, what we heard from survey respondents was jarring: only 29%
believe their organisations are using data well, dropping to 19%
amongst senior professionals. In an age where everyone knows that
data is the new oil, where are we going wrong? We’ll take a closer look at
this question, but one thing is clear:
The rise of big data has been nothing short of revolutionary. But more
is needed. A seismic shift in culture and strategy is required if we are
to truly view data as an asset rather than a liability. And the shift has to
start at the top, with more business leaders ‘getting’ data.
Sales and marketing teams are already reaping the benefits, as a
360-degree view into customer behaviour is one of the most common
applications for data. (Not to mention it’s a win for the consumer
as well.) Whilst the use of data to improve commercial outcomes is
coming into its own, it’s evident to us there’s a huge gap in using data
to improve operational efficiency internally. We consider this one of
the biggest areas of untapped potential as data adoption approaches
maturity.
What will the successful implementation of an IM strategy entail in the
future? As many technology-driven trends as we may see emerging, the
human element is more important than ever. Organisations need highly
specialised employees who possess not only technical ability, but
influencing skills and emotional intelligence as well.
Overall, the survey confirms to us that any barriers to optimising
the power of data lie not in hardware or software limitations, but in
putting together a team that can collaborate to create value for your
organisation.
Mark Dexter
...
Managing Director
KDR Recruitment
3. We’ve got the data – why aren’t we using it well?
With the majorityof survey respondents rating their
use of data from ‘average’ to ‘poor,’ there is clearly a disconnect
between the gathering of data and its application – or at least, there’s
the perception of one. More worryingly, this is more true for senior
management including IT Directors, CIOs and Heads of BI and Data.
So where is this disconnect happening? What are the perceived
obstacles to successful data application? Three strong themes
emerge from the comments made by survey respondents:
• Quality (Is the data clean, robust, reliable?)
• Strategy (What is the data’s purpose?)
• Culture (Are IT, Information Management, and the C-suite all on the
same page?)
We believe this to be the most critical issue the world of data is
currently facing. Without meaningful analytics and application, data
exists in a vacuum and will not help an organisation make better
business decisions. Companies will struggle to quantify the value
data adds, whilst the executive suite will lose confidence in KPI
reports and business cases.
The world of data is at a tipping point. Never before have we had such
technical power to gather, process, and store data. The clear next step
is making sense of it all, but to do this, Information Management and
the executive suite must be aligned in their objectives.
‘Data is often an
afterthought but needs to
be central. Linking data to
business processes (through
both purpose and content)
remains a challenge.’
Survey respondent
PROBLEM SOLUTION
QUALITY
Decentralised data;
unrestricted access
Increased standardisation, governance and security
STRATEGY Too much data
Alignment of business objectives; focusing on agility
rather than quantity; scalability
CULTURE
Lack of buy-in from
management
Knowledge sharing, influencing skills,
realistic expectations
Other respondentsSenior professionals%
Extremely well
Fairly well
About average
Fairly poorly
Extremely poorly
How well does your
organisation use data
4. Using data to improve performance: what’s ahead?
Overall, data ismost commonly being used to deliver
insight around three areas: profitability, customer behaviour and
cost of sales – not particularly surprising, given these are areas that
present strong ROI for data infrastructure spending.
Broken out by sector, we see some differences:
• Retailers focus on customer data
• Financial services are more concerned with costs and compliance
• IT/software sector are leveraging data for new product development
Fairly predictable, but it leaves us to wonder whether a narrow focus
on one area could be restricting the ability of companies to truly
harness the full power of their data. We see an opportunity here for
employers to recruit from outside their sector to bring in fresh new
perspectives.
Sales and marketing remain the clear focus in 2015, as enterprises
deploy data as a strategic asset to increase customer engagement
and explore options for growth. However, it’s noteworthy that internal
operational issues – such as the HR function, the supply chain,
process engineering, fraud detection or inventory – trail well behind
externally focused areas. Going forward, enterprises must make
data as critical to operations as it is to sales; unlocking the untapped
potential to improve efficiency in-house can contribute just as much
to the bottom line.
‘Businesses are still
developing their
understanding around
the power of intellectual
supplier spend and market
data. I tend to encounter a
lot of businesses who have
no consolidated supplier
performance reporting. This
means they don’t identify
synergies, efficiencies or
inefficiencies and don’t
realise the benefits of
consolidation or a complete
strategic change.’
Procurement Director
Hub Strategic Communications
Understanding customer behaviour
Understanding profitability
Understanding cost of sales
New product development
Setting pricing
To ensure legal compliance
Monitoring competitor activity
Managing staff retention
Other
Where do you use data to
improve performance?
0
10
20
30
40
50
60
70
80
%
5. Where is data most used to improve performance by sector?
Manufacturing
18%
to measure
profitability
Retail
25%
to understand
customer
behaviour
Energy/
utilities
24%
to understand
customer
behaviour
Financial
services
18%
to measure
cost of sales
IT/software
20%
to develop
new products
6. Where should we be using data?
Where data is being used vs where respondents think it should be used
Between 50 and 60% of survey respondents are using data to
understand customer behaviour and profitability but nearly 80%
believe they should be. Of course, the two are linked in that better
insight into your customers should lead to improved profitability, as
long as those insights translate to product or service development,
more compelling propositions and appropriate spend on most and least
valuable customers.
Many analysts struggle with the challenges of customer data whilst
sales and marketing departments recognise the need for hyper-
personalisation but lack the skills to implement such strategies. Those
who are successful in this area are able to pinpoint the customer
characteristics that lead to profitability (previous buying behaviour,
original lead source, brand engagement and so on) and filter out the
red herrings. They’ll then use this information to improve the customer
experience, whether that’s as simple as using the communication
channel of their preference or a game-changing new product launch.
0
10
20
30
40
50
60
70
80
%
Current use
Should be used
Understanding
customer
behaviour
Understanding
profitability
Understanding
cost of sales
Setting
pricing
New product
development
Monitoring
competitor
activity
To ensure
legal
compliance
Managing
staff
retention
Other
7. Overcoming roadblocks calls for a change in culture
What are thebiggest barriers to implementing an
Information Management strategy? Whilst lack of resources or budget
can be a matter of cost constraints, they can also be a result of the
most common answer: lack of buy-in from the C-suite. The perception
that management doesn’t “get” data is still prevalent, and in light
of some of the comments left by respondents, we see evidence
of a divide between IT and Information Management as well. All
signposts point to cultural change as a key driver for data adoption
going forward – the hurdles are not technological, but are centred
around creating alignment of purpose and process among senior
management, IT and data management specialists.
These are gaps that call for increased investment, not in hardware
or software, but in the human element. Enterprises must focus on
creating a culture that places value on influencing skills, emotional
intelligence, communication and collaboration in order to propel their
data efforts forward and realise real results.
CULTURE f “IT push back” f “IT think IM is bogus, that if it’s
not technology, it’s not IT” f “No one understands the business
requirements as they’re too broad to get your head around”
SCALABILITY f “The size of the organisation is the biggest barrier”
f “The complexity of disparate data in a diversified group”
PROCESS f “Poor data quality is the biggest barrier to
wide-scale adoption” f “There’s a disconnect between data
process and understanding”
Lack of buy-in from C-suite/leadership
Lack of resources
Lack of budget
Lack of skills
IM doesn’t understand business requirements
Lack of buy-in from BI users
Hardware issues
Software issues
Other
22.6%
20%
18.3%
11.3%
8.7%
4.3%
2.6%
2.6%
9.6%
The barriers to implementing an
informational Management strategy
‘An organisation that has
successfully embedded IM
strategy into its 5 year growth
plan is Nationwide Building
Society. The Executive
Board acknowledged the
need for a best-in-class IM
function and made it one of
their 10 building blocks for
success. One of the benefits
has been that customer-
facing employees now get a
complete and accurate picture
of clients, allowing them to
proactively suggest products
that make sense for them.’
8. The Data Manager of the future
A data managermust meet very specific, highly
specialised technical requirements. But as is becoming clear, a
truly robust organisation thrives on communication, teamwork,
problem-solving and project/process management.
That’s why enterprises are keen to build teams that can bring
those values to the forefront, and are increasingly interested in
a candidate’s soft skills. It’s a brave new world in which the old
paradigm that power equals influence is being inverted – instead,
as the traditional top-down management model gives way to a
more lateral structure, those with influence will wield more power.
The ideal data manager of the future is strong communicator, with a
solid grasp of the organisation’s needs, sharp commercial acumen,
and the capacity to comprehend big picture challenges – and
visualise solutions.
Where this falls down
Due to this lack of communication skills, we see many
organisations engaging external consultancies to build business
cases for IM projects.
The consequence is that the skills remain with the consultancy and
aren’t transferred to the internal team. If this sounds familiar to
you, consider how to include this knowledge transfer in your next
scope of work.
The importance of long-term vision
We were interested to see a divergence in views on this topic.
While 24% of respondents considered it the most important
quality for data managers to have, 13% thought it least important.
We found it worrying that nearly 1 in 7 respondents appear not to
think data managers need to understand the context of their work
and how it contributes to the organisation at large.
By continuing to engage in recruitment practices that focus solely
on technical skills, companies will miss out on the unlimited
potential of their data efforts.
Technical skills
Data science
Architecture
Analysis
SQL
Big data
Soft skills
Influencing
Long term vision
Listening
Questioning
Adaptability
9. Optimising data quality – it’s not just about process
Tighter controls, stewardshipand governance,
clear methodologies and benchmarks – these are some common
answers to the question “What can we do to improve data quality?”
As might be expected, these types of answers offer valuable insight
into process improvements that must be implemented in order to
optimise data quality.
Whilst quality control over the sourcing, input, processing and
storage of data obviously will remain essential, it’s noteworthy that
the two most effective ways to improve were not process-oriented,
not technological in nature, but once again called for the human
element. Engaging users is considered critical to the success of the
data function, as is creating clear definitions of the business purposes
of data.
As we’ve said before, data is not just about gathering as much
information as possible – it’s about using good information to inform
business decisions that will drive your success as an organisation.
Enterprises must ensure that valuable resources are being allocated
in such a way that data is given the proper framework and context to
drive results.
This cannot happen without communication, consensus and
collaboration from a team with a shared vision. When data is used
well, it creates a momentum, one that will see more stakeholders on
board with the concept that data quality should be the gold standard
for the entire organisation, not just the IT and IM departments.
These results clearly show that organisations are becoming more mature in their approach
to managing data quality, but data professionals shouldn’t rest on their laurels yet, as there
is clearly still some educating to be done. It is encouraging that people are realising that
throwing money at the problem does not improve data quality and engaging the users of the
data is now recognised as one of the most effective methods.
However it is slightly disappointing that organisations are still not fully understanding the
strategic value in implementing data governance/appointing a data stewardship function
and it seems that the short-term tactical fix of cleaning your data is still more popular than it
should be (as opposed to fixing the underlying cause of the problem).
Nicola Askham
The Data Governance Coach
Engaging users of data
Clear definition of what data is needed
Tight controls on how data can be input
Clean your data
Use of a data dictionary
Appoint a data stewardship function
Ensure you have benchmarks for measuring change
Being careful about the use of inputed data
Investment
What are the most
effective ways to
improve data quality?
Rank
1
2
3
4
5
6
7
8
9
10. Software vendors: make it easy, or lose the sale
In analysing oursurvey results, we didn’t see much to
indicate that technological issues were behind any obstacles to
successful adoption of a data management strategy.
Nevertheless, we wanted to explore what those in the industry were
looking for when choosing new information software.
One thing became abundantly clear – new software must integrate
easily into existing infrastructure and systems. This is far and
away the most important consideration for users, who also want that
same flexibility to extend to customisation options and reporting
functionalities.
Traditional standards such as pricing, the reputation of the vendor,
and additional consulting services are deemed far less important in
this new climate. This could be the result of a plethora of available
products on the market, or a trend toward increasing budgets for data
spend.
Within the self-service data integration market, established players
such as IBM with their PureData offering, Informatica’s Rev product or
Microsoft’s Powerquery for Excel have the marketing clout to give the
specialists such as Trifacta, Paxata and Matillion a run for their money.
Whatever the technology choice though, without establishing and
working within an IT led governance framework, you risk ending up
with silos of data in a similar way that multiple versions of conflicting
data are often found within most businesses’ Excel estate.
Ease of integration
Amount of customisation possible
Reporting functionality
Price
Speed of integration
Reputation of vendor
Availability of external consultancy
What is most important to
you when selecting new
information software?
50%
7.9%
7%
5.3%
12.3%
16.7%
0.9%